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2026-07-12 16:31:15 | INFO | ML | === RUN START ===
2026-07-12 16:31:15 | INFO | ML | project=ML
2026-07-12 16:31:15 | INFO | ML | repo_dir=ml-03-classification
2026-07-12 16:31:15 | INFO | ML | python=3.14.2
2026-07-12 16:31:15 | INFO | ML | os=Windows 11
2026-07-12 16:31:15 | INFO | ML | shell=powershell
2026-07-12 16:31:15 | INFO | ML | cwd=.
2026-07-12 16:31:15 | INFO | ML | github_actions=False
2026-07-12 16:31:15 | INFO | ML | === RUN START ===
2026-07-12 16:31:15 | INFO | ML | project=ML
2026-07-12 16:31:15 | INFO | ML | repo_dir=ml-03-classification
2026-07-12 16:31:15 | INFO | ML | python=3.14.2
2026-07-12 16:31:15 | INFO | ML | os=Windows 11
2026-07-12 16:31:15 | INFO | ML | shell=powershell
2026-07-12 16:31:15 | INFO | ML | cwd=.
2026-07-12 16:31:15 | INFO | ML | github_actions=False
2026-07-12 16:31:15 | INFO | ML | ========================
2026-07-12 16:31:15 | INFO | ML | START main()
2026-07-12 16:31:15 | INFO | ML | ========================
2026-07-12 16:31:15 | INFO | ML | Load dataset..............
2026-07-12 16:31:15 | INFO | ML | Loading dataset: hours_scores_case
2026-07-12 16:31:15 | INFO | ML | Loaded: 10 rows, 6 columns
2026-07-12 16:31:15 | DEBUG | ML |
hours_studied practice_quizzes attendance_pct sleep_hours prior_score score
0 2.0 1 72 6.0 58 62
1 3.5 2 80 6.5 61 68
2 4.0 3 85 7.0 64 72
3 5.0 3 88 7.5 66 76
4 6.0 4 90 7.0 70 81
2026-07-12 16:31:15 | INFO | ML | Inspect dataset...........
2026-07-12 16:31:15 | INFO | ML | Column names
2026-07-12 16:31:15 | DEBUG | ML | ['hours_studied', 'practice_quizzes', 'attendance_pct', 'sleep_hours', 'prior_score', 'score']
2026-07-12 16:31:15 | INFO | ML | DataFrame info
2026-07-12 16:31:15 | INFO | ML | Dataset shape: 10 rows, 6 columns
2026-07-12 16:31:15 | INFO | ML | Check data quality........
2026-07-12 16:31:15 | INFO | ML | Missing values by column
2026-07-12 16:31:15 | DEBUG | ML |
hours_studied 0
practice_quizzes 0
attendance_pct 0
sleep_hours 0
prior_score 0
score 0
dtype: int64
2026-07-12 16:31:15 | INFO | ML | Duplicate row count: 0
2026-07-12 16:31:15 | INFO | ML | Create clean view.........
2026-07-12 16:31:15 | INFO | ML | Creating clean modeling view
2026-07-12 16:31:15 | INFO | ML | Clean view: 10 rows, 6 columns
2026-07-12 16:31:15 | INFO | ML | Train supervised model....
2026-07-12 16:31:15 | INFO | ML | Training LinearRegression model
2026-07-12 16:31:15 | INFO | ML | Mean absolute error: 0.48
2026-07-12 16:31:15 | INFO | ML | R-squared: 1.00
2026-07-12 16:31:15 | INFO | ML | Predict one case..........
2026-07-12 16:31:15 | INFO | ML | Predicting one new case
2026-07-12 16:31:15 | INFO | ML | New case:
hours_studied practice_quizzes attendance_pct sleep_hours prior_score
0 6.5 4 92 7.0 72
2026-07-12 16:31:15 | INFO | ML | Predicted score: 83.4
2026-07-12 16:31:15 | INFO | ML | Create charts.............
2026-07-12 16:31:15 | INFO | ML | Creating chart: hours studied vs score
2026-07-12 16:31:16 | INFO | ML | Creating chart: model coefficients
2026-07-12 16:31:16 | INFO | ML | Got a figure Figure(900x500) and axes Axes(0.125,0.11;0.775x0.77) from plt.subplots().
2026-07-12 16:31:16 | INFO | ML | Summarize workflow........
2026-07-12 16:31:16 | INFO | ML | ========================
2026-07-12 16:31:16 | INFO | ML | SUMMARY
2026-07-12 16:31:16 | INFO | ML | ========================
2026-07-12 16:31:16 | INFO | ML | Dataset: hours_scores_case
2026-07-12 16:31:16 | INFO | ML | Original rows: 10
2026-07-12 16:31:16 | INFO | ML | Clean rows: 10
2026-07-12 16:31:16 | INFO | ML | Features: ['hours_studied', 'practice_quizzes', 'attendance_pct', 'sleep_hours', 'prior_score']
2026-07-12 16:31:16 | INFO | ML | Target: score
2026-07-12 16:31:16 | INFO | ML | ----- in a script, call plt.show() once at the end to display all charts -----
2026-07-12 16:31:16 | INFO | ML | ----- in a script, CLOSE the chart windows with the close button to CONTINUE -----
2026-07-12 16:31:24 | INFO | ML | Workflow complete
2026-07-12 16:31:24 | INFO | ML | IMPORTANT: This script creates chart windows.
2026-07-12 16:31:24 | INFO | ML | Close chart windows and terminate this process with CTRL+c as needed.
2026-07-12 16:31:24 | INFO | ML | ========================
2026-07-12 16:31:24 | INFO | ML | Executed successfully!
2026-07-12 16:31:24 | INFO | ML | ========================
2026-07-12 16:33:35 | INFO | ML | === RUN START ===
2026-07-12 16:33:35 | INFO | ML | project=ML
2026-07-12 16:33:35 | INFO | ML | repo_dir=ml-03-classification
2026-07-12 16:33:35 | INFO | ML | python=3.14.2
2026-07-12 16:33:35 | INFO | ML | os=Windows 11
2026-07-12 16:33:35 | INFO | ML | shell=powershell
2026-07-12 16:33:35 | INFO | ML | cwd=.
2026-07-12 16:33:35 | INFO | ML | github_actions=False
2026-07-12 16:37:31 | INFO | ML | === RUN START ===
2026-07-12 16:37:31 | INFO | ML | project=ML
2026-07-12 16:37:31 | INFO | ML | repo_dir=ml-03-classification
2026-07-12 16:37:31 | INFO | ML | python=3.14.2
2026-07-12 16:37:31 | INFO | ML | os=Windows 11
2026-07-12 16:37:31 | INFO | ML | shell=powershell
2026-07-12 16:37:31 | INFO | ML | cwd=.
2026-07-12 16:37:31 | INFO | ML | github_actions=False
2026-07-12 17:30:47 | INFO | M03 | === RUN START ===
2026-07-12 17:30:47 | INFO | M03 | project=M03
2026-07-12 17:30:47 | INFO | M03 | repo_dir=ml-03-classification
2026-07-12 17:30:47 | INFO | M03 | python=3.14.2
2026-07-12 17:30:47 | INFO | M03 | os=Windows 11
2026-07-12 17:30:47 | INFO | M03 | shell=powershell
2026-07-12 17:30:47 | INFO | M03 | cwd=notebooks
2026-07-12 17:30:47 | INFO | M03 | github_actions=False
2026-07-12 17:30:47 | INFO | M03 | Confirming installation:
2026-07-12 17:30:47 | INFO | M03 | python: 3.14.2
2026-07-12 17:30:47 | INFO | M03 | pandas: 3.0.3
2026-07-12 17:30:47 | INFO | M03 | numpy: 2.5.1
2026-07-12 17:30:47 | INFO | M03 | scikit-learn: 1.9.0
2026-07-12 17:30:47 | INFO | M03 | seaborn: 0.13.2
2026-07-12 17:30:47 | INFO | M03 | matplotlib: 3.11.0
2026-07-12 17:30:47 | INFO | M03 | Loading dataset: penguins
2026-07-12 17:30:47 | INFO | M03 | Loaded: 344 rows (instances), 7 columns
2026-07-12 17:30:47 | INFO | M03 | Original rows: 344
2026-07-12 17:30:47 | INFO | M03 | Model rows: 342
2026-07-12 17:30:47 | INFO | M03 | Classes in target 'species': ['Adelie', 'Chinstrap', 'Gentoo']
2026-07-12 17:30:47 | DEBUG | M03 | Class counts:
species
Adelie 151
Gentoo 123
Chinstrap 68
Name: count, dtype: int64
2026-07-12 17:30:47 | INFO | M03 | Train instances: 273
2026-07-12 17:30:47 | INFO | M03 | Test instances: 69
2026-07-12 17:30:47 | INFO | M03 | Fitting DecisionTreeClassifier(max_depth=3)
2026-07-12 17:30:47 | INFO | M03 | Test accuracy: 0.986
2026-07-12 17:30:47 | INFO | M03 | Per-class precision / recall / F1:
2026-07-12 17:30:47 | DEBUG | M03 |
precision recall f1-score support
Adelie 0.97 1.00 0.98 30
Chinstrap 1.00 0.93 0.96 14
Gentoo 1.00 1.00 1.00 25
accuracy 0.99 69
macro avg 0.99 0.98 0.98 69
weighted avg 0.99 0.99 0.99 69
2026-07-12 17:30:47 | INFO | M03 | Showing confusion matrix (rows = actual, cols = predicted)
2026-07-12 17:30:47 | DEBUG | M03 | depth= 1 train=0.791 test=0.797
2026-07-12 17:30:47 | DEBUG | M03 | depth= 2 train=0.960 test=0.986
2026-07-12 17:30:47 | DEBUG | M03 | depth= 3 train=0.967 test=0.986
2026-07-12 17:30:47 | DEBUG | M03 | depth= 4 train=0.989 test=1.000
2026-07-12 17:30:47 | DEBUG | M03 | depth= 5 train=0.996 test=1.000
2026-07-12 17:30:47 | DEBUG | M03 | depth= 6 train=0.996 test=1.000
2026-07-12 17:30:47 | DEBUG | M03 | depth= 7 train=1.000 test=1.000
2026-07-12 17:30:47 | DEBUG | M03 | depth= 8 train=1.000 test=1.000
2026-07-12 17:30:47 | DEBUG | M03 | depth= 9 train=1.000 test=1.000
2026-07-12 17:30:47 | DEBUG | M03 | depth=10 train=1.000 test=1.000
2026-07-12 17:30:47 | DEBUG | M03 | depth=11 train=1.000 test=1.000
2026-07-12 17:30:47 | DEBUG | M03 | depth=12 train=1.000 test=1.000
2026-07-12 17:30:47 | INFO | M03 | ========================
2026-07-12 17:30:47 | INFO | M03 | SUMMARY
2026-07-12 17:30:47 | INFO | M03 | ========================
2026-07-12 17:30:47 | INFO | M03 | Dataset: penguins
2026-07-12 17:30:47 | INFO | M03 | Target: species (classification)
2026-07-12 17:30:47 | INFO | M03 | Features: ['bill_length_mm', 'bill_depth_mm', 'flipper_length_mm', 'body_mass_g']
2026-07-12 17:30:47 | INFO | M03 | Model: DecisionTreeClassifier(max_depth=3)
2026-07-12 17:30:47 | INFO | M03 | ========================
2026-07-12 19:12:39 | INFO | M03 | === RUN START ===
2026-07-12 19:12:39 | INFO | M03 | project=M03
2026-07-12 19:12:39 | INFO | M03 | repo_dir=ml-03-classification
2026-07-12 19:12:39 | INFO | M03 | python=3.14.2
2026-07-12 19:12:39 | INFO | M03 | os=Windows 11
2026-07-12 19:12:39 | INFO | M03 | shell=powershell
2026-07-12 19:12:39 | INFO | M03 | cwd=notebooks
2026-07-12 19:12:39 | INFO | M03 | github_actions=False
2026-07-12 19:12:39 | INFO | M03 | Confirming installation:
2026-07-12 19:12:39 | INFO | M03 | python: 3.14.2
2026-07-12 19:12:39 | INFO | M03 | pandas: 3.0.3
2026-07-12 19:12:39 | INFO | M03 | numpy: 2.5.1
2026-07-12 19:12:39 | INFO | M03 | scikit-learn: 1.9.0
2026-07-12 19:12:39 | INFO | M03 | seaborn: 0.13.2
2026-07-12 19:12:39 | INFO | M03 | matplotlib: 3.11.0
2026-07-12 19:12:39 | INFO | M03 | Loading dataset: penguins
2026-07-12 19:12:39 | INFO | M03 | Loaded: 344 rows (instances), 7 columns
2026-07-12 19:12:39 | INFO | M03 | Original rows: 344
2026-07-12 19:12:39 | INFO | M03 | Model rows: 342
2026-07-12 19:12:39 | INFO | M03 | Classes in target 'species': ['Adelie', 'Chinstrap', 'Gentoo']
2026-07-12 19:12:39 | DEBUG | M03 | Class counts:
species
Adelie 151
Gentoo 123
Chinstrap 68
Name: count, dtype: int64
2026-07-12 19:12:39 | INFO | M03 | Train instances: 273
2026-07-12 19:12:39 | INFO | M03 | Test instances: 69
2026-07-12 19:12:39 | INFO | M03 | Fitting DecisionTreeClassifier(max_depth=3)
2026-07-12 19:12:39 | INFO | M03 | Test accuracy: 0.986
2026-07-12 19:12:39 | INFO | M03 | Per-class precision / recall / F1:
2026-07-12 19:12:39 | DEBUG | M03 |
precision recall f1-score support
Adelie 0.97 1.00 0.98 30
Chinstrap 1.00 0.93 0.96 14
Gentoo 1.00 1.00 1.00 25
accuracy 0.99 69
macro avg 0.99 0.98 0.98 69
weighted avg 0.99 0.99 0.99 69
2026-07-12 19:12:39 | INFO | M03 | Showing confusion matrix (rows = actual, cols = predicted)
2026-07-12 19:12:39 | DEBUG | M03 | depth= 1 train=0.791 test=0.797
2026-07-12 19:12:39 | DEBUG | M03 | depth= 2 train=0.960 test=0.986
2026-07-12 19:12:39 | DEBUG | M03 | depth= 3 train=0.967 test=0.986
2026-07-12 19:12:39 | DEBUG | M03 | depth= 4 train=0.989 test=1.000
2026-07-12 19:12:39 | DEBUG | M03 | depth= 5 train=0.996 test=1.000
2026-07-12 19:12:39 | DEBUG | M03 | depth= 6 train=0.996 test=1.000
2026-07-12 19:12:39 | DEBUG | M03 | depth= 7 train=1.000 test=1.000
2026-07-12 19:12:39 | DEBUG | M03 | depth= 8 train=1.000 test=1.000
2026-07-12 19:12:39 | DEBUG | M03 | depth= 9 train=1.000 test=1.000
2026-07-12 19:12:39 | DEBUG | M03 | depth=10 train=1.000 test=1.000
2026-07-12 19:12:39 | DEBUG | M03 | depth=11 train=1.000 test=1.000
2026-07-12 19:12:39 | DEBUG | M03 | depth=12 train=1.000 test=1.000
2026-07-12 19:12:39 | INFO | M03 | ========================
2026-07-12 19:12:39 | INFO | M03 | SUMMARY
2026-07-12 19:12:39 | INFO | M03 | ========================
2026-07-12 19:12:39 | INFO | M03 | Dataset: penguins
2026-07-12 19:12:39 | INFO | M03 | Target: species (classification)
2026-07-12 19:12:39 | INFO | M03 | Features: ['bill_length_mm', 'bill_depth_mm', 'flipper_length_mm', 'body_mass_g']
2026-07-12 19:12:39 | INFO | M03 | Model: DecisionTreeClassifier(max_depth=3)
2026-07-12 19:12:39 | INFO | M03 | ========================
2026-07-12 19:13:18 | INFO | ML | === RUN START ===
2026-07-12 19:13:18 | INFO | ML | project=ML
2026-07-12 19:13:18 | INFO | ML | repo_dir=ml-03-classification
2026-07-12 19:13:18 | INFO | ML | python=3.14.2
2026-07-12 19:13:18 | INFO | ML | os=Windows 11
2026-07-12 19:13:18 | INFO | ML | shell=powershell
2026-07-12 19:13:18 | INFO | ML | cwd=.
2026-07-12 19:13:18 | INFO | ML | github_actions=False
2026-07-12 20:37:20 | INFO | ML | === RUN START ===
2026-07-12 20:37:20 | INFO | ML | project=ML
2026-07-12 20:37:20 | INFO | ML | repo_dir=ml-03-classification
2026-07-12 20:37:20 | INFO | ML | python=3.14.2
2026-07-12 20:37:20 | INFO | ML | os=Windows 11
2026-07-12 20:37:20 | INFO | ML | shell=powershell
2026-07-12 20:37:20 | INFO | ML | cwd=.
2026-07-12 20:37:20 | INFO | ML | github_actions=False
2026-07-12 20:37:20 | INFO | ML | === RUN START ===
2026-07-12 20:37:20 | INFO | ML | project=ML
2026-07-12 20:37:20 | INFO | ML | repo_dir=ml-03-classification
2026-07-12 20:37:20 | INFO | ML | python=3.14.2
2026-07-12 20:37:20 | INFO | ML | os=Windows 11
2026-07-12 20:37:20 | INFO | ML | shell=powershell
2026-07-12 20:37:20 | INFO | ML | cwd=.
2026-07-12 20:37:20 | INFO | ML | github_actions=False
2026-07-12 20:37:20 | INFO | ML | ========================
2026-07-12 20:37:20 | INFO | ML | START main()
2026-07-12 20:37:20 | INFO | ML | ========================
2026-07-12 20:37:20 | INFO | ML | Load dataset..............
2026-07-12 20:37:20 | INFO | ML | Loading dataset: hours_scores_case
2026-07-12 20:37:20 | INFO | ML | Loaded: 10 rows, 6 columns
2026-07-12 20:37:20 | DEBUG | ML |
hours_studied practice_quizzes attendance_pct sleep_hours prior_score score
0 2.0 1 72 6.0 58 62
1 3.5 2 80 6.5 61 68
2 4.0 3 85 7.0 64 72
3 5.0 3 88 7.5 66 76
4 6.0 4 90 7.0 70 81
2026-07-12 20:37:20 | INFO | ML | Inspect dataset...........
2026-07-12 20:37:20 | INFO | ML | Column names
2026-07-12 20:37:20 | DEBUG | ML | ['hours_studied', 'practice_quizzes', 'attendance_pct', 'sleep_hours', 'prior_score', 'score']
2026-07-12 20:37:20 | INFO | ML | DataFrame info
2026-07-12 20:37:20 | INFO | ML | Dataset shape: 10 rows, 6 columns
2026-07-12 20:37:20 | INFO | ML | Check data quality........
2026-07-12 20:37:20 | INFO | ML | Missing values by column
2026-07-12 20:37:20 | DEBUG | ML |
hours_studied 0
practice_quizzes 0
attendance_pct 0
sleep_hours 0
prior_score 0
score 0
dtype: int64
2026-07-12 20:37:20 | INFO | ML | Duplicate row count: 0
2026-07-12 20:37:20 | INFO | ML | Create clean view.........
2026-07-12 20:37:20 | INFO | ML | Creating clean modeling view
2026-07-12 20:37:20 | INFO | ML | Clean view: 10 rows, 6 columns
2026-07-12 20:37:20 | INFO | ML | Train supervised model....
2026-07-12 20:37:20 | INFO | ML | Training LinearRegression model
2026-07-12 20:37:20 | INFO | ML | Mean absolute error: 0.48
2026-07-12 20:37:20 | INFO | ML | R-squared: 1.00
2026-07-12 20:37:20 | INFO | ML | Predict one case..........
2026-07-12 20:37:20 | INFO | ML | Predicting one new case
2026-07-12 20:37:20 | INFO | ML | New case:
hours_studied practice_quizzes attendance_pct sleep_hours prior_score
0 6.5 4 92 7.0 72
2026-07-12 20:37:20 | INFO | ML | Predicted score: 83.4
2026-07-12 20:37:20 | INFO | ML | Create charts.............
2026-07-12 20:37:20 | INFO | ML | Creating chart: hours studied vs score
2026-07-12 20:37:20 | INFO | ML | Creating chart: model coefficients
2026-07-12 20:37:20 | INFO | ML | Got a figure Figure(900x500) and axes Axes(0.125,0.11;0.775x0.77) from plt.subplots().
2026-07-12 20:37:20 | INFO | ML | Summarize workflow........
2026-07-12 20:37:20 | INFO | ML | ========================
2026-07-12 20:37:20 | INFO | ML | SUMMARY
2026-07-12 20:37:20 | INFO | ML | ========================
2026-07-12 20:37:20 | INFO | ML | Dataset: hours_scores_case
2026-07-12 20:37:20 | INFO | ML | Original rows: 10
2026-07-12 20:37:20 | INFO | ML | Clean rows: 10
2026-07-12 20:37:20 | INFO | ML | Features: ['hours_studied', 'practice_quizzes', 'attendance_pct', 'sleep_hours', 'prior_score']
2026-07-12 20:37:20 | INFO | ML | Target: score
2026-07-12 20:37:20 | INFO | ML | ----- in a script, call plt.show() once at the end to display all charts -----
2026-07-12 20:37:20 | INFO | ML | ----- in a script, CLOSE the chart windows with the close button to CONTINUE -----
2026-07-12 20:37:23 | INFO | ML | Workflow complete
2026-07-12 20:37:23 | INFO | ML | IMPORTANT: This script creates chart windows.
2026-07-12 20:37:23 | INFO | ML | Close chart windows and terminate this process with CTRL+c as needed.
2026-07-12 20:37:23 | INFO | ML | ========================
2026-07-12 20:37:23 | INFO | ML | Executed successfully!
2026-07-12 20:37:23 | INFO | ML | ========================
2026-07-12 20:37:38 | INFO | M03 | === RUN START ===
2026-07-12 20:37:38 | INFO | M03 | project=M03
2026-07-12 20:37:38 | INFO | M03 | repo_dir=ml-03-classification
2026-07-12 20:37:38 | INFO | M03 | python=3.14.2
2026-07-12 20:37:38 | INFO | M03 | os=Windows 11
2026-07-12 20:37:38 | INFO | M03 | shell=powershell
2026-07-12 20:37:38 | INFO | M03 | cwd=notebooks
2026-07-12 20:37:38 | INFO | M03 | github_actions=False
2026-07-12 20:37:38 | INFO | M03 | Confirming installation:
2026-07-12 20:37:38 | INFO | M03 | python: 3.14.2
2026-07-12 20:37:38 | INFO | M03 | pandas: 3.0.3
2026-07-12 20:37:38 | INFO | M03 | numpy: 2.5.1
2026-07-12 20:37:38 | INFO | M03 | scikit-learn: 1.9.0
2026-07-12 20:37:38 | INFO | M03 | seaborn: 0.13.2
2026-07-12 20:37:38 | INFO | M03 | matplotlib: 3.11.0
2026-07-12 20:37:38 | INFO | M03 | Loading dataset: penguins
2026-07-12 20:37:38 | INFO | M03 | Loaded: 344 rows (instances), 7 columns
2026-07-12 20:37:38 | INFO | M03 | Original rows: 344
2026-07-12 20:37:38 | INFO | M03 | Model rows: 342
2026-07-12 20:37:38 | INFO | M03 | Classes in target 'species': ['Adelie', 'Chinstrap', 'Gentoo']
2026-07-12 20:37:38 | DEBUG | M03 | Class counts:
species
Adelie 151
Gentoo 123
Chinstrap 68
Name: count, dtype: int64
2026-07-12 20:37:38 | INFO | M03 | Train instances: 273
2026-07-12 20:37:38 | INFO | M03 | Test instances: 69
2026-07-12 20:37:38 | INFO | M03 | Fitting DecisionTreeClassifier(max_depth=3)
2026-07-12 20:37:38 | INFO | M03 | Test accuracy: 0.986
2026-07-12 20:37:38 | INFO | M03 | Per-class precision / recall / F1:
2026-07-12 20:37:38 | DEBUG | M03 |
precision recall f1-score support
Adelie 0.97 1.00 0.98 30
Chinstrap 1.00 0.93 0.96 14
Gentoo 1.00 1.00 1.00 25
accuracy 0.99 69
macro avg 0.99 0.98 0.98 69
weighted avg 0.99 0.99 0.99 69
2026-07-12 20:37:38 | INFO | M03 | Showing confusion matrix (rows = actual, cols = predicted)
2026-07-12 20:37:38 | DEBUG | M03 | depth= 1 train=0.791 test=0.797
2026-07-12 20:37:38 | DEBUG | M03 | depth= 2 train=0.960 test=0.986
2026-07-12 20:37:38 | DEBUG | M03 | depth= 3 train=0.967 test=0.986
2026-07-12 20:37:38 | DEBUG | M03 | depth= 4 train=0.989 test=1.000
2026-07-12 20:37:38 | DEBUG | M03 | depth= 5 train=0.996 test=1.000
2026-07-12 20:37:38 | DEBUG | M03 | depth= 6 train=0.996 test=1.000
2026-07-12 20:37:38 | DEBUG | M03 | depth= 7 train=1.000 test=1.000
2026-07-12 20:37:38 | DEBUG | M03 | depth= 8 train=1.000 test=1.000
2026-07-12 20:37:38 | DEBUG | M03 | depth= 9 train=1.000 test=1.000
2026-07-12 20:37:38 | DEBUG | M03 | depth=10 train=1.000 test=1.000
2026-07-12 20:37:38 | DEBUG | M03 | depth=11 train=1.000 test=1.000
2026-07-12 20:37:38 | DEBUG | M03 | depth=12 train=1.000 test=1.000
2026-07-12 20:37:38 | INFO | M03 | ========================
2026-07-12 20:37:38 | INFO | M03 | SUMMARY
2026-07-12 20:37:38 | INFO | M03 | ========================
2026-07-12 20:37:38 | INFO | M03 | Dataset: penguins
2026-07-12 20:37:38 | INFO | M03 | Target: species (classification)
2026-07-12 20:37:38 | INFO | M03 | Features: ['bill_length_mm', 'bill_depth_mm', 'flipper_length_mm', 'body_mass_g']
2026-07-12 20:37:38 | INFO | M03 | Model: DecisionTreeClassifier(max_depth=3)
2026-07-12 20:37:38 | INFO | M03 | ========================
2026-07-12 20:41:27 | INFO | ML | === RUN START ===
2026-07-12 20:41:27 | INFO | ML | project=ML
2026-07-12 20:41:27 | INFO | ML | repo_dir=ml-03-classification
2026-07-12 20:41:27 | INFO | ML | python=3.14.2
2026-07-12 20:41:27 | INFO | ML | os=Windows 11
2026-07-12 20:41:27 | INFO | ML | shell=powershell
2026-07-12 20:41:27 | INFO | ML | cwd=.
2026-07-12 20:41:27 | INFO | ML | github_actions=False
2026-07-17 16:26:30 | INFO | M03 | === RUN START ===
2026-07-17 16:26:30 | INFO | M03 | project=M03
2026-07-17 16:26:30 | INFO | M03 | repo_dir=ml-03-classification
2026-07-17 16:26:30 | INFO | M03 | python=3.14.2
2026-07-17 16:26:30 | INFO | M03 | os=Windows 11
2026-07-17 16:26:30 | INFO | M03 | shell=powershell
2026-07-17 16:26:30 | INFO | M03 | cwd=notebooks
2026-07-17 16:26:30 | INFO | M03 | github_actions=False
2026-07-17 16:26:30 | INFO | M03 | Confirming installation:
2026-07-17 16:26:30 | INFO | M03 | python: 3.14.2
2026-07-17 16:26:30 | INFO | M03 | pandas: 3.0.3
2026-07-17 16:26:30 | INFO | M03 | numpy: 2.5.1
2026-07-17 16:26:30 | INFO | M03 | scikit-learn: 1.9.0
2026-07-17 16:26:30 | INFO | M03 | seaborn: 0.13.2
2026-07-17 16:26:30 | INFO | M03 | matplotlib: 3.11.0
2026-07-17 16:26:30 | INFO | M03 | Loading dataset: penguins
2026-07-17 16:26:30 | INFO | M03 | Loaded: 344 rows (instances), 7 columns
2026-07-17 16:26:30 | INFO | M03 | Original rows: 344
2026-07-17 16:26:30 | INFO | M03 | Model rows: 342
2026-07-17 16:26:30 | INFO | M03 | Classes in target 'species': ['Adelie', 'Chinstrap', 'Gentoo']
2026-07-17 16:26:30 | DEBUG | M03 | Class counts:
species
Adelie 151
Gentoo 123
Chinstrap 68
Name: count, dtype: int64
2026-07-17 16:26:30 | INFO | M03 | Train instances: 273
2026-07-17 16:26:30 | INFO | M03 | Test instances: 69
2026-07-17 16:26:30 | INFO | M03 | Fitting DecisionTreeClassifier(max_depth=3)
2026-07-17 16:26:30 | INFO | M03 | Test accuracy: 0.986
2026-07-17 16:26:30 | INFO | M03 | Per-class precision / recall / F1:
2026-07-17 16:26:30 | DEBUG | M03 |
precision recall f1-score support
Adelie 0.97 1.00 0.98 30
Chinstrap 1.00 0.93 0.96 14
Gentoo 1.00 1.00 1.00 25
accuracy 0.99 69
macro avg 0.99 0.98 0.98 69
weighted avg 0.99 0.99 0.99 69
2026-07-17 16:26:30 | INFO | M03 | Showing confusion matrix (rows = actual, cols = predicted)
2026-07-17 16:26:31 | DEBUG | M03 | depth= 1 train=0.791 test=0.797
2026-07-17 16:26:31 | DEBUG | M03 | depth= 2 train=0.960 test=0.986
2026-07-17 16:26:31 | DEBUG | M03 | depth= 3 train=0.967 test=0.986
2026-07-17 16:26:31 | DEBUG | M03 | depth= 4 train=0.989 test=1.000
2026-07-17 16:26:31 | DEBUG | M03 | depth= 5 train=0.996 test=1.000
2026-07-17 16:26:31 | DEBUG | M03 | depth= 6 train=0.996 test=1.000
2026-07-17 16:26:31 | DEBUG | M03 | depth= 7 train=1.000 test=1.000
2026-07-17 16:26:31 | DEBUG | M03 | depth= 8 train=1.000 test=1.000
2026-07-17 16:26:31 | DEBUG | M03 | depth= 9 train=1.000 test=1.000
2026-07-17 16:26:31 | DEBUG | M03 | depth=10 train=1.000 test=1.000
2026-07-17 16:26:31 | DEBUG | M03 | depth=11 train=1.000 test=1.000
2026-07-17 16:26:31 | DEBUG | M03 | depth=12 train=1.000 test=1.000
2026-07-17 16:26:31 | INFO | M03 | ========================
2026-07-17 16:26:31 | INFO | M03 | SUMMARY
2026-07-17 16:26:31 | INFO | M03 | ========================
2026-07-17 16:26:31 | INFO | M03 | Dataset: penguins
2026-07-17 16:26:31 | INFO | M03 | Target: species (classification)
2026-07-17 16:26:31 | INFO | M03 | Features: ['bill_length_mm', 'bill_depth_mm', 'flipper_length_mm', 'body_mass_g']
2026-07-17 16:26:31 | INFO | M03 | Model: DecisionTreeClassifier(max_depth=3)
2026-07-17 16:26:31 | INFO | M03 | ========================
2026-07-17 18:37:41 | INFO | M03 | === RUN START ===
2026-07-17 18:37:41 | INFO | M03 | project=M03
2026-07-17 18:37:41 | INFO | M03 | repo_dir=ml-03-classification
2026-07-17 18:37:41 | INFO | M03 | python=3.14.2
2026-07-17 18:37:41 | INFO | M03 | os=Windows 11
2026-07-17 18:37:41 | INFO | M03 | shell=powershell
2026-07-17 18:37:41 | INFO | M03 | cwd=notebooks
2026-07-17 18:37:41 | INFO | M03 | github_actions=False
2026-07-17 18:37:41 | INFO | M03 | Confirming installation:
2026-07-17 18:37:41 | INFO | M03 | python: 3.14.2
2026-07-17 18:37:41 | INFO | M03 | pandas: 3.0.3
2026-07-17 18:37:41 | INFO | M03 | numpy: 2.5.1
2026-07-17 18:37:41 | INFO | M03 | scikit-learn: 1.9.0
2026-07-17 18:37:41 | INFO | M03 | seaborn: 0.13.2
2026-07-17 18:37:41 | INFO | M03 | matplotlib: 3.11.0
2026-07-17 18:37:41 | INFO | M03 | Loading dataset: sex
2026-07-17 18:41:35 | INFO | M03 | === RUN START ===
2026-07-17 18:41:35 | INFO | M03 | project=M03
2026-07-17 18:41:35 | INFO | M03 | repo_dir=ml-03-classification
2026-07-17 18:41:35 | INFO | M03 | python=3.14.2
2026-07-17 18:41:35 | INFO | M03 | os=Windows 11
2026-07-17 18:41:35 | INFO | M03 | shell=powershell
2026-07-17 18:41:35 | INFO | M03 | cwd=notebooks
2026-07-17 18:41:35 | INFO | M03 | github_actions=False
2026-07-17 18:41:35 | INFO | M03 | Confirming installation:
2026-07-17 18:41:35 | INFO | M03 | python: 3.14.2
2026-07-17 18:41:35 | INFO | M03 | pandas: 3.0.3
2026-07-17 18:41:35 | INFO | M03 | numpy: 2.5.1
2026-07-17 18:41:35 | INFO | M03 | scikit-learn: 1.9.0
2026-07-17 18:41:35 | INFO | M03 | seaborn: 0.13.2
2026-07-17 18:41:35 | INFO | M03 | matplotlib: 3.11.0
2026-07-17 18:41:35 | INFO | M03 | Loading dataset: penguins
2026-07-17 18:41:35 | INFO | M03 | Loaded: 344 rows (instances), 7 columns
2026-07-17 18:41:35 | INFO | M03 | Original rows: 344
2026-07-17 18:41:35 | INFO | M03 | Model rows: 333
2026-07-17 18:41:35 | INFO | M03 | Classes in target 'sex': ['Female', 'Male']
2026-07-17 18:41:35 | DEBUG | M03 | Class counts:
sex
Male 168
Female 165
Name: count, dtype: int64
2026-07-17 18:41:35 | INFO | M03 | Train instances: 266
2026-07-17 18:41:35 | INFO | M03 | Test instances: 67
2026-07-17 18:41:35 | INFO | M03 | Fitting DecisionTreeClassifier(max_depth=3)
2026-07-17 18:41:35 | INFO | M03 | Test accuracy: 0.836
2026-07-17 18:41:35 | INFO | M03 | Per-class precision / recall / F1:
2026-07-17 18:41:35 | DEBUG | M03 |
precision recall f1-score support
Female 0.92 0.73 0.81 33
Male 0.78 0.94 0.85 34
accuracy 0.84 67
macro avg 0.85 0.83 0.83 67
weighted avg 0.85 0.84 0.83 67
2026-07-17 18:41:35 | INFO | M03 | Showing confusion matrix (rows = actual, cols = predicted)
2026-07-17 18:41:36 | DEBUG | M03 | depth= 1 train=0.726 test=0.716
2026-07-17 18:41:36 | DEBUG | M03 | depth= 2 train=0.891 test=0.821
2026-07-17 18:41:36 | DEBUG | M03 | depth= 3 train=0.940 test=0.836
2026-07-17 18:41:36 | DEBUG | M03 | depth= 4 train=0.951 test=0.851
2026-07-17 18:41:36 | DEBUG | M03 | depth= 5 train=0.966 test=0.851
2026-07-17 18:41:36 | DEBUG | M03 | depth= 6 train=0.977 test=0.851
2026-07-17 18:41:36 | DEBUG | M03 | depth= 7 train=0.981 test=0.836
2026-07-17 18:41:36 | DEBUG | M03 | depth= 8 train=0.996 test=0.821
2026-07-17 18:41:36 | DEBUG | M03 | depth= 9 train=0.996 test=0.821
2026-07-17 18:41:36 | DEBUG | M03 | depth=10 train=1.000 test=0.821
2026-07-17 18:41:36 | DEBUG | M03 | depth=11 train=1.000 test=0.821
2026-07-17 18:41:36 | DEBUG | M03 | depth=12 train=1.000 test=0.821
2026-07-17 18:41:36 | INFO | M03 | ========================
2026-07-17 18:41:36 | INFO | M03 | SUMMARY
2026-07-17 18:41:36 | INFO | M03 | ========================
2026-07-17 18:41:36 | INFO | M03 | Dataset: penguins
2026-07-17 18:41:36 | INFO | M03 | Target: sex (classification)
2026-07-17 18:41:36 | INFO | M03 | Features: ['bill_length_mm', 'bill_depth_mm', 'flipper_length_mm', 'body_mass_g']
2026-07-17 18:41:36 | INFO | M03 | Model: DecisionTreeClassifier(max_depth=3)
2026-07-17 18:41:36 | INFO | M03 | ========================
2026-07-17 19:15:07 | INFO | ML | === RUN START ===
2026-07-17 19:15:07 | INFO | ML | project=ML
2026-07-17 19:15:07 | INFO | ML | repo_dir=ml-03-classification
2026-07-17 19:15:07 | INFO | ML | python=3.14.2
2026-07-17 19:15:07 | INFO | ML | os=Windows 11
2026-07-17 19:15:07 | INFO | ML | shell=powershell
2026-07-17 19:15:07 | INFO | ML | cwd=.
2026-07-17 19:15:07 | INFO | ML | github_actions=False
2026-07-18 09:19:53 | INFO | M03-STUDENTS | === RUN START ===
2026-07-18 09:19:53 | INFO | M03-STUDENTS | project=M03
2026-07-18 09:19:53 | INFO | M03-STUDENTS | repo_dir=ml-03-classification
2026-07-18 09:19:53 | INFO | M03-STUDENTS | python=3.14.2
2026-07-18 09:19:53 | INFO | M03-STUDENTS | os=Windows 11
2026-07-18 09:19:53 | INFO | M03-STUDENTS | shell=powershell
2026-07-18 09:19:53 | INFO | M03-STUDENTS | cwd=notebooks
2026-07-18 09:19:53 | INFO | M03-STUDENTS | github_actions=False
2026-07-18 09:19:53 | INFO | M03-STUDENTS | Confirming installation:
2026-07-18 09:19:53 | INFO | M03-STUDENTS | python: 3.14.2
2026-07-18 09:19:53 | INFO | M03-STUDENTS | pandas: 3.0.3
2026-07-18 09:19:53 | INFO | M03-STUDENTS | numpy: 2.5.1
2026-07-18 09:19:53 | INFO | M03-STUDENTS | scikit-learn: 1.9.0
2026-07-18 09:19:53 | INFO | M03-STUDENTS | seaborn: 0.13.2
2026-07-18 09:19:53 | INFO | M03-STUDENTS | matplotlib: 3.11.0
2026-07-18 09:19:53 | INFO | M03-STUDENTS | Loading dataset: penguins
2026-07-18 09:19:53 | INFO | M03-STUDENTS | Loaded: 344 rows (instances), 7 columns
2026-07-18 09:19:53 | INFO | M03-STUDENTS | Original rows: 344
2026-07-18 09:19:53 | INFO | M03-STUDENTS | Model rows: 333
2026-07-18 09:19:53 | INFO | M03-STUDENTS | Classes in target 'sex': ['Female', 'Male']
2026-07-18 09:19:53 | DEBUG | M03-STUDENTS | Class counts:
sex
Male 168
Female 165
Name: count, dtype: int64
2026-07-18 09:19:53 | INFO | M03-STUDENTS | Train instances: 266
2026-07-18 09:19:53 | INFO | M03-STUDENTS | Test instances: 67
2026-07-18 09:19:53 | INFO | M03-STUDENTS | Fitting DecisionTreeClassifier(max_depth=3)
2026-07-18 09:19:53 | INFO | M03-STUDENTS | Test accuracy: 0.836
2026-07-18 09:19:53 | INFO | M03-STUDENTS | Per-class precision / recall / F1:
2026-07-18 09:19:53 | DEBUG | M03-STUDENTS |
precision recall f1-score support
Female 0.92 0.73 0.81 33
Male 0.78 0.94 0.85 34
accuracy 0.84 67
macro avg 0.85 0.83 0.83 67
weighted avg 0.85 0.84 0.83 67
2026-07-18 09:19:53 | INFO | M03-STUDENTS | Showing confusion matrix (rows = actual, cols = predicted)
2026-07-18 09:19:53 | DEBUG | M03-STUDENTS | depth= 1 train=0.726 test=0.716
2026-07-18 09:19:53 | DEBUG | M03-STUDENTS | depth= 2 train=0.891 test=0.821
2026-07-18 09:19:53 | DEBUG | M03-STUDENTS | depth= 3 train=0.940 test=0.836
2026-07-18 09:19:53 | DEBUG | M03-STUDENTS | depth= 4 train=0.951 test=0.851
2026-07-18 09:19:53 | DEBUG | M03-STUDENTS | depth= 5 train=0.966 test=0.851
2026-07-18 09:19:53 | DEBUG | M03-STUDENTS | depth= 6 train=0.977 test=0.851
2026-07-18 09:19:53 | DEBUG | M03-STUDENTS | depth= 7 train=0.981 test=0.836
2026-07-18 09:19:53 | DEBUG | M03-STUDENTS | depth= 8 train=0.996 test=0.821
2026-07-18 09:19:53 | DEBUG | M03-STUDENTS | depth= 9 train=0.996 test=0.821
2026-07-18 09:19:53 | DEBUG | M03-STUDENTS | depth=10 train=1.000 test=0.821
2026-07-18 09:19:53 | DEBUG | M03-STUDENTS | depth=11 train=1.000 test=0.821
2026-07-18 09:19:53 | DEBUG | M03-STUDENTS | depth=12 train=1.000 test=0.821
2026-07-18 09:19:53 | INFO | M03-STUDENTS | ========================
2026-07-18 09:19:53 | INFO | M03-STUDENTS | SUMMARY
2026-07-18 09:19:53 | INFO | M03-STUDENTS | ========================
2026-07-18 09:19:53 | INFO | M03-STUDENTS | Dataset: penguins
2026-07-18 09:19:53 | INFO | M03-STUDENTS | Target: sex (classification)
2026-07-18 09:19:53 | INFO | M03-STUDENTS | Features: ['bill_length_mm', 'bill_depth_mm', 'flipper_length_mm', 'body_mass_g']
2026-07-18 09:19:53 | INFO | M03-STUDENTS | Model: DecisionTreeClassifier(max_depth=3)
2026-07-18 09:19:53 | INFO | M03-STUDENTS | ========================
2026-07-18 16:45:50 | INFO | M03-STUDENTS | === RUN START ===
2026-07-18 16:45:50 | INFO | M03-STUDENTS | project=M03
2026-07-18 16:45:50 | INFO | M03-STUDENTS | repo_dir=ml-03-classification
2026-07-18 16:45:50 | INFO | M03-STUDENTS | python=3.14.2
2026-07-18 16:45:50 | INFO | M03-STUDENTS | os=Windows 11
2026-07-18 16:45:50 | INFO | M03-STUDENTS | shell=powershell
2026-07-18 16:45:50 | INFO | M03-STUDENTS | cwd=notebooks
2026-07-18 16:45:50 | INFO | M03-STUDENTS | github_actions=False
2026-07-18 16:45:50 | INFO | M03-STUDENTS | Confirming installation:
2026-07-18 16:45:50 | INFO | M03-STUDENTS | python: 3.14.2
2026-07-18 16:45:50 | INFO | M03-STUDENTS | pandas: 3.0.3
2026-07-18 16:45:50 | INFO | M03-STUDENTS | numpy: 2.5.1
2026-07-18 16:45:50 | INFO | M03-STUDENTS | scikit-learn: 1.9.0
2026-07-18 16:45:50 | INFO | M03-STUDENTS | seaborn: 0.13.2
2026-07-18 16:45:50 | INFO | M03-STUDENTS | matplotlib: 3.11.0
2026-07-18 17:19:53 | INFO | M03-STUDENTS | Loading dataset: student-mat
2026-07-18 17:19:53 | INFO | M03-STUDENTS | Loaded: 395 rows (instances), 33 columns
2026-07-18 17:19:53 | INFO | M03-STUDENTS | Original rows: 395
2026-07-18 17:19:53 | INFO | M03-STUDENTS | Model rows: 395
2026-07-18 17:19:53 | INFO | M03-STUDENTS | Classes in target 'result': ['fail', 'pass']
2026-07-18 17:19:53 | DEBUG | M03-STUDENTS | Class counts:
result
pass 265
fail 130
Name: count, dtype: int64
2026-07-18 17:24:08 | INFO | M03-STUDENTS | Train instances: 316
2026-07-18 17:24:08 | INFO | M03-STUDENTS | Test instances: 79
2026-07-18 17:33:34 | INFO | M03-STUDENTS | Per-column completeness and type:
2026-07-18 17:33:34 | INFO | M03-STUDENTS | school str present=100.0% missing=0
2026-07-18 17:33:34 | INFO | M03-STUDENTS | sex str present=100.0% missing=0
2026-07-18 17:33:34 | INFO | M03-STUDENTS | age int64 present=100.0% missing=0
2026-07-18 17:33:34 | INFO | M03-STUDENTS | address str present=100.0% missing=0
2026-07-18 17:33:34 | INFO | M03-STUDENTS | famsize str present=100.0% missing=0
2026-07-18 17:33:34 | INFO | M03-STUDENTS | Pstatus str present=100.0% missing=0
2026-07-18 17:33:34 | INFO | M03-STUDENTS | Medu int64 present=100.0% missing=0
2026-07-18 17:33:34 | INFO | M03-STUDENTS | Fedu int64 present=100.0% missing=0
2026-07-18 17:33:34 | INFO | M03-STUDENTS | Mjob str present=100.0% missing=0
2026-07-18 17:33:34 | INFO | M03-STUDENTS | Fjob str present=100.0% missing=0
2026-07-18 17:33:34 | INFO | M03-STUDENTS | reason str present=100.0% missing=0
2026-07-18 17:33:34 | INFO | M03-STUDENTS | guardian str present=100.0% missing=0
2026-07-18 17:33:34 | INFO | M03-STUDENTS | traveltime int64 present=100.0% missing=0
2026-07-18 17:33:34 | INFO | M03-STUDENTS | studytime int64 present=100.0% missing=0
2026-07-18 17:33:34 | INFO | M03-STUDENTS | failures int64 present=100.0% missing=0
2026-07-18 17:33:34 | INFO | M03-STUDENTS | schoolsup str present=100.0% missing=0
2026-07-18 17:33:34 | INFO | M03-STUDENTS | famsup str present=100.0% missing=0
2026-07-18 17:33:34 | INFO | M03-STUDENTS | paid str present=100.0% missing=0
2026-07-18 17:33:34 | INFO | M03-STUDENTS | activities str present=100.0% missing=0
2026-07-18 17:33:34 | INFO | M03-STUDENTS | nursery str present=100.0% missing=0
2026-07-18 17:33:34 | INFO | M03-STUDENTS | higher str present=100.0% missing=0
2026-07-18 17:33:34 | INFO | M03-STUDENTS | internet str present=100.0% missing=0
2026-07-18 17:33:34 | INFO | M03-STUDENTS | romantic str present=100.0% missing=0
2026-07-18 17:33:34 | INFO | M03-STUDENTS | famrel int64 present=100.0% missing=0
2026-07-18 17:33:34 | INFO | M03-STUDENTS | freetime int64 present=100.0% missing=0
2026-07-18 17:33:34 | INFO | M03-STUDENTS | goout int64 present=100.0% missing=0
2026-07-18 17:33:34 | INFO | M03-STUDENTS | Dalc int64 present=100.0% missing=0
2026-07-18 17:33:34 | INFO | M03-STUDENTS | Walc int64 present=100.0% missing=0
2026-07-18 17:33:34 | INFO | M03-STUDENTS | health int64 present=100.0% missing=0
2026-07-18 17:33:34 | INFO | M03-STUDENTS | absences int64 present=100.0% missing=0
2026-07-18 17:33:34 | INFO | M03-STUDENTS | G1 int64 present=100.0% missing=0
2026-07-18 17:33:34 | INFO | M03-STUDENTS | G2 int64 present=100.0% missing=0
2026-07-18 17:33:34 | INFO | M03-STUDENTS | G3 int64 present=100.0% missing=0
2026-07-18 17:33:34 | INFO | M03-STUDENTS | result str present=100.0% missing=0
2026-07-18 17:33:34 | INFO | M03-STUDENTS | Numeric summary of the feature columns (spread and outliers):
2026-07-18 17:33:34 | DEBUG | M03-STUDENTS |
age Medu Fedu traveltime studytime failures famrel freetime goout \
count 395.000000 395.000000 395.000000 395.000000 395.000000 395.000000 395.000000 395.000000 395.000000
mean 16.696203 2.749367 2.521519 1.448101 2.035443 0.334177 3.944304 3.235443 3.108861
std 1.276043 1.094735 1.088201 0.697505 0.839240 0.743651 0.896659 0.998862 1.113278
min 15.000000 0.000000 0.000000 1.000000 1.000000 0.000000 1.000000 1.000000 1.000000
25% 16.000000 2.000000 2.000000 1.000000 1.000000 0.000000 4.000000 3.000000 2.000000
50% 17.000000 3.000000 2.000000 1.000000 2.000000 0.000000 4.000000 3.000000 3.000000
75% 18.000000 4.000000 3.000000 2.000000 2.000000 0.000000 5.000000 4.000000 4.000000
max 22.000000 4.000000 4.000000 4.000000 4.000000 3.000000 5.000000 5.000000 5.000000
Dalc Walc health absences
count 395.000000 395.000000 395.000000 395.000000
mean 1.481013 2.291139 3.554430 5.708861
std 0.890741 1.287897 1.390303 8.003096
min 1.000000 1.000000 1.000000 0.000000
25% 1.000000 1.000000 3.000000 0.000000
50% 1.000000 2.000000 4.000000 4.000000
75% 2.000000 3.000000 5.000000 8.000000
max 5.000000 5.000000 5.000000 75.000000
2026-07-18 17:33:35 | INFO | M03-STUDENTS | absences: max=75, median=4.0
2026-07-18 17:33:35 | INFO | M03-STUDENTS | absences over 20: 15 students
2026-07-18 17:41:46 | INFO | M03-STUDENTS | Fitting DecisionTreeClassifier(max_depth=3)
2026-07-18 17:42:47 | INFO | M03-STUDENTS | Test accuracy: 0.658
2026-07-18 17:42:47 | INFO | M03-STUDENTS | Per-class precision / recall / F1:
2026-07-18 17:42:47 | DEBUG | M03-STUDENTS |
precision recall f1-score support
fail 0.44 0.15 0.23 26
pass 0.69 0.91 0.78 53
accuracy 0.66 79
macro avg 0.57 0.53 0.50 79
weighted avg 0.61 0.66 0.60 79
2026-07-18 17:42:47 | INFO | M03-STUDENTS | Showing confusion matrix (rows = actual, cols = predicted)
2026-07-18 17:43:57 | DEBUG | M03-STUDENTS | depth= 1 train=0.737 test=0.671
2026-07-18 17:43:57 | DEBUG | M03-STUDENTS | depth= 2 train=0.750 test=0.658
2026-07-18 17:43:57 | DEBUG | M03-STUDENTS | depth= 3 train=0.769 test=0.658
2026-07-18 17:43:57 | DEBUG | M03-STUDENTS | depth= 4 train=0.797 test=0.646
2026-07-18 17:43:57 | DEBUG | M03-STUDENTS | depth= 5 train=0.826 test=0.646
2026-07-18 17:43:57 | DEBUG | M03-STUDENTS | depth= 6 train=0.845 test=0.582
2026-07-18 17:43:57 | DEBUG | M03-STUDENTS | depth= 7 train=0.880 test=0.582
2026-07-18 17:43:57 | DEBUG | M03-STUDENTS | depth= 8 train=0.908 test=0.620
2026-07-18 17:43:57 | DEBUG | M03-STUDENTS | depth= 9 train=0.934 test=0.595
2026-07-18 17:43:57 | DEBUG | M03-STUDENTS | depth=10 train=0.949 test=0.595
2026-07-18 17:43:57 | DEBUG | M03-STUDENTS | depth=11 train=0.978 test=0.532
2026-07-18 17:43:57 | DEBUG | M03-STUDENTS | depth=12 train=0.987 test=0.582
2026-07-18 18:30:47 | INFO | ML | === RUN START ===
2026-07-18 18:30:47 | INFO | ML | project=ML
2026-07-18 18:30:47 | INFO | ML | repo_dir=ml-03-classification
2026-07-18 18:30:47 | INFO | ML | python=3.14.2
2026-07-18 18:30:47 | INFO | ML | os=Windows 11
2026-07-18 18:30:47 | INFO | ML | shell=powershell
2026-07-18 18:30:47 | INFO | ML | cwd=.
2026-07-18 18:30:47 | INFO | ML | github_actions=False
2026-07-19 08:08:26 | INFO | M03-STUDENTS | === RUN START ===
2026-07-19 08:08:26 | INFO | M03-STUDENTS | project=M03
2026-07-19 08:08:26 | INFO | M03-STUDENTS | repo_dir=ml-03-classification
2026-07-19 08:08:26 | INFO | M03-STUDENTS | python=3.14.2
2026-07-19 08:08:26 | INFO | M03-STUDENTS | os=Windows 11
2026-07-19 08:08:26 | INFO | M03-STUDENTS | shell=powershell
2026-07-19 08:08:26 | INFO | M03-STUDENTS | cwd=notebooks
2026-07-19 08:08:26 | INFO | M03-STUDENTS | github_actions=False
2026-07-19 08:08:26 | INFO | M03-STUDENTS | Confirming installation:
2026-07-19 08:08:26 | INFO | M03-STUDENTS | python: 3.14.2
2026-07-19 08:08:26 | INFO | M03-STUDENTS | pandas: 3.0.3
2026-07-19 08:08:26 | INFO | M03-STUDENTS | numpy: 2.5.1
2026-07-19 08:08:26 | INFO | M03-STUDENTS | scikit-learn: 1.9.0
2026-07-19 08:08:26 | INFO | M03-STUDENTS | seaborn: 0.13.2
2026-07-19 08:08:26 | INFO | M03-STUDENTS | matplotlib: 3.11.0
2026-07-19 08:08:50 | INFO | M03-STUDENTS | Loading dataset: student-mat
2026-07-19 08:08:50 | INFO | M03-STUDENTS | Loaded: 395 rows (instances), 33 columns
2026-07-19 08:08:50 | INFO | M03-STUDENTS | Original rows: 395
2026-07-19 08:08:50 | INFO | M03-STUDENTS | Model rows: 395
2026-07-19 08:08:50 | INFO | M03-STUDENTS | Classes in target 'result': ['fail', 'pass']
2026-07-19 08:08:50 | DEBUG | M03-STUDENTS | Class counts:
result
pass 265
fail 130
Name: count, dtype: int64
2026-07-19 08:08:50 | INFO | M03-STUDENTS | Per-column completeness and type:
2026-07-19 08:08:50 | INFO | M03-STUDENTS | school str present=100.0% missing=0
2026-07-19 08:08:50 | INFO | M03-STUDENTS | sex str present=100.0% missing=0
2026-07-19 08:08:50 | INFO | M03-STUDENTS | age int64 present=100.0% missing=0
2026-07-19 08:08:50 | INFO | M03-STUDENTS | address str present=100.0% missing=0
2026-07-19 08:08:50 | INFO | M03-STUDENTS | famsize str present=100.0% missing=0
2026-07-19 08:08:50 | INFO | M03-STUDENTS | Pstatus str present=100.0% missing=0
2026-07-19 08:08:50 | INFO | M03-STUDENTS | Medu int64 present=100.0% missing=0
2026-07-19 08:08:50 | INFO | M03-STUDENTS | Fedu int64 present=100.0% missing=0
2026-07-19 08:08:50 | INFO | M03-STUDENTS | Mjob str present=100.0% missing=0
2026-07-19 08:08:50 | INFO | M03-STUDENTS | Fjob str present=100.0% missing=0
2026-07-19 08:08:50 | INFO | M03-STUDENTS | reason str present=100.0% missing=0
2026-07-19 08:08:50 | INFO | M03-STUDENTS | guardian str present=100.0% missing=0
2026-07-19 08:08:50 | INFO | M03-STUDENTS | traveltime int64 present=100.0% missing=0
2026-07-19 08:08:50 | INFO | M03-STUDENTS | studytime int64 present=100.0% missing=0
2026-07-19 08:08:50 | INFO | M03-STUDENTS | failures int64 present=100.0% missing=0
2026-07-19 08:08:50 | INFO | M03-STUDENTS | schoolsup str present=100.0% missing=0
2026-07-19 08:08:50 | INFO | M03-STUDENTS | famsup str present=100.0% missing=0
2026-07-19 08:08:50 | INFO | M03-STUDENTS | paid str present=100.0% missing=0
2026-07-19 08:08:50 | INFO | M03-STUDENTS | activities str present=100.0% missing=0
2026-07-19 08:08:50 | INFO | M03-STUDENTS | nursery str present=100.0% missing=0
2026-07-19 08:08:50 | INFO | M03-STUDENTS | higher str present=100.0% missing=0
2026-07-19 08:08:50 | INFO | M03-STUDENTS | internet str present=100.0% missing=0
2026-07-19 08:08:50 | INFO | M03-STUDENTS | romantic str present=100.0% missing=0
2026-07-19 08:08:50 | INFO | M03-STUDENTS | famrel int64 present=100.0% missing=0
2026-07-19 08:08:50 | INFO | M03-STUDENTS | freetime int64 present=100.0% missing=0
2026-07-19 08:08:50 | INFO | M03-STUDENTS | goout int64 present=100.0% missing=0
2026-07-19 08:08:50 | INFO | M03-STUDENTS | Dalc int64 present=100.0% missing=0
2026-07-19 08:08:50 | INFO | M03-STUDENTS | Walc int64 present=100.0% missing=0
2026-07-19 08:08:50 | INFO | M03-STUDENTS | health int64 present=100.0% missing=0
2026-07-19 08:08:50 | INFO | M03-STUDENTS | absences int64 present=100.0% missing=0
2026-07-19 08:08:50 | INFO | M03-STUDENTS | G1 int64 present=100.0% missing=0
2026-07-19 08:08:50 | INFO | M03-STUDENTS | G2 int64 present=100.0% missing=0
2026-07-19 08:08:50 | INFO | M03-STUDENTS | G3 int64 present=100.0% missing=0
2026-07-19 08:08:50 | INFO | M03-STUDENTS | result str present=100.0% missing=0
2026-07-19 08:08:50 | INFO | M03-STUDENTS | Numeric summary of the feature columns (spread and outliers):
2026-07-19 08:08:50 | DEBUG | M03-STUDENTS |
Medu Fedu studytime failures absences G1 G2
count 395.000000 395.000000 395.000000 395.000000 395.000000 395.000000 395.000000
mean 2.749367 2.521519 2.035443 0.334177 5.708861 10.908861 10.713924
std 1.094735 1.088201 0.839240 0.743651 8.003096 3.319195 3.761505
min 0.000000 0.000000 1.000000 0.000000 0.000000 3.000000 0.000000
25% 2.000000 2.000000 1.000000 0.000000 0.000000 8.000000 9.000000
50% 3.000000 2.000000 2.000000 0.000000 4.000000 11.000000 11.000000
75% 4.000000 3.000000 2.000000 0.000000 8.000000 13.000000 13.000000
max 4.000000 4.000000 4.000000 3.000000 75.000000 19.000000 19.000000
2026-07-19 08:08:50 | INFO | M03-STUDENTS | absences: max=75, median=4.0
2026-07-19 08:08:50 | INFO | M03-STUDENTS | absences over 20: 15 students
2026-07-19 08:15:00 | INFO | M03-STUDENTS | Loading dataset: student-mat
2026-07-19 08:15:00 | INFO | M03-STUDENTS | Loaded: 395 rows (instances), 33 columns
2026-07-19 08:15:00 | INFO | M03-STUDENTS | Per-column completeness and type:
2026-07-19 08:15:00 | INFO | M03-STUDENTS | school str present=100.0% missing=0
2026-07-19 08:15:00 | INFO | M03-STUDENTS | sex str present=100.0% missing=0
2026-07-19 08:15:00 | INFO | M03-STUDENTS | age int64 present=100.0% missing=0
2026-07-19 08:15:00 | INFO | M03-STUDENTS | address str present=100.0% missing=0
2026-07-19 08:15:00 | INFO | M03-STUDENTS | famsize str present=100.0% missing=0
2026-07-19 08:15:00 | INFO | M03-STUDENTS | Pstatus str present=100.0% missing=0
2026-07-19 08:15:00 | INFO | M03-STUDENTS | Medu int64 present=100.0% missing=0
2026-07-19 08:15:00 | INFO | M03-STUDENTS | Fedu int64 present=100.0% missing=0
2026-07-19 08:15:00 | INFO | M03-STUDENTS | Mjob str present=100.0% missing=0
2026-07-19 08:15:00 | INFO | M03-STUDENTS | Fjob str present=100.0% missing=0
2026-07-19 08:15:00 | INFO | M03-STUDENTS | reason str present=100.0% missing=0
2026-07-19 08:15:00 | INFO | M03-STUDENTS | guardian str present=100.0% missing=0
2026-07-19 08:15:00 | INFO | M03-STUDENTS | traveltime int64 present=100.0% missing=0
2026-07-19 08:15:00 | INFO | M03-STUDENTS | studytime int64 present=100.0% missing=0
2026-07-19 08:15:00 | INFO | M03-STUDENTS | failures int64 present=100.0% missing=0
2026-07-19 08:15:00 | INFO | M03-STUDENTS | schoolsup str present=100.0% missing=0
2026-07-19 08:15:00 | INFO | M03-STUDENTS | famsup str present=100.0% missing=0
2026-07-19 08:15:00 | INFO | M03-STUDENTS | paid str present=100.0% missing=0
2026-07-19 08:15:00 | INFO | M03-STUDENTS | activities str present=100.0% missing=0
2026-07-19 08:15:00 | INFO | M03-STUDENTS | nursery str present=100.0% missing=0
2026-07-19 08:15:00 | INFO | M03-STUDENTS | higher str present=100.0% missing=0
2026-07-19 08:15:00 | INFO | M03-STUDENTS | internet str present=100.0% missing=0
2026-07-19 08:15:00 | INFO | M03-STUDENTS | romantic str present=100.0% missing=0
2026-07-19 08:15:00 | INFO | M03-STUDENTS | famrel int64 present=100.0% missing=0
2026-07-19 08:15:00 | INFO | M03-STUDENTS | freetime int64 present=100.0% missing=0
2026-07-19 08:15:00 | INFO | M03-STUDENTS | goout int64 present=100.0% missing=0
2026-07-19 08:15:00 | INFO | M03-STUDENTS | Dalc int64 present=100.0% missing=0
2026-07-19 08:15:00 | INFO | M03-STUDENTS | Walc int64 present=100.0% missing=0
2026-07-19 08:15:00 | INFO | M03-STUDENTS | health int64 present=100.0% missing=0
2026-07-19 08:15:00 | INFO | M03-STUDENTS | absences int64 present=100.0% missing=0
2026-07-19 08:15:00 | INFO | M03-STUDENTS | G1 int64 present=100.0% missing=0
2026-07-19 08:15:00 | INFO | M03-STUDENTS | G2 int64 present=100.0% missing=0
2026-07-19 08:15:00 | INFO | M03-STUDENTS | G3 int64 present=100.0% missing=0
2026-07-19 08:15:00 | INFO | M03-STUDENTS | Numeric summary of the candidate feature columns (spread and outliers):
2026-07-19 08:15:00 | DEBUG | M03-STUDENTS |
Medu Fedu studytime failures absences G1 G2
count 395.000000 395.000000 395.000000 395.000000 395.000000 395.000000 395.000000
mean 2.749367 2.521519 2.035443 0.334177 5.708861 10.908861 10.713924
std 1.094735 1.088201 0.839240 0.743651 8.003096 3.319195 3.761505
min 0.000000 0.000000 1.000000 0.000000 0.000000 3.000000 0.000000
25% 2.000000 2.000000 1.000000 0.000000 0.000000 8.000000 9.000000
50% 3.000000 2.000000 2.000000 0.000000 4.000000 11.000000 11.000000
75% 4.000000 3.000000 2.000000 0.000000 8.000000 13.000000 13.000000
max 4.000000 4.000000 4.000000 3.000000 75.000000 19.000000 19.000000
2026-07-19 08:15:00 | INFO | M03-STUDENTS | absences: max=75, median=4.0
2026-07-19 08:15:00 | INFO | M03-STUDENTS | absences over 20: 15 students
2026-07-19 08:15:00 | INFO | M03-STUDENTS | Original rows: 395
2026-07-19 08:15:00 | INFO | M03-STUDENTS | Model rows: 395
2026-07-19 08:15:00 | INFO | M03-STUDENTS | Classes in target 'result': ['fail', 'pass']
2026-07-19 08:15:00 | DEBUG | M03-STUDENTS | Class counts:
result
pass 265
fail 130
Name: count, dtype: int64
2026-07-19 08:26:44 | INFO | M03-STUDENTS | Train instances: 316
2026-07-19 08:26:44 | INFO | M03-STUDENTS | Test instances: 79
2026-07-19 08:28:09 | INFO | M03-STUDENTS | Fitting one DecisionTreeClassifier(max_depth=3) per quarter
2026-07-19 08:28:09 | INFO | M03-STUDENTS | Fit three trees: fall (no grades), winter (+G1), spring (+G1, G2)
2026-07-19 10:20:11 | INFO | M03-STUDENTS | --- Fall --- accuracy = 0.658
2026-07-19 10:20:11 | INFO | M03-STUDENTS | Per-class precision / recall / F1:
2026-07-19 10:20:11 | DEBUG | M03-STUDENTS |
precision recall f1-score support
fail 0.44 0.15 0.23 26
pass 0.69 0.91 0.78 53
accuracy 0.66 79
macro avg 0.57 0.53 0.50 79
weighted avg 0.61 0.66 0.60 79
2026-07-19 10:20:12 | INFO | M03-STUDENTS | --- Winter --- accuracy = 0.835
2026-07-19 10:20:12 | INFO | M03-STUDENTS | Per-class precision / recall / F1:
2026-07-19 10:20:12 | DEBUG | M03-STUDENTS |
precision recall f1-score support
fail 0.78 0.69 0.73 26
pass 0.86 0.91 0.88 53
accuracy 0.84 79
macro avg 0.82 0.80 0.81 79
weighted avg 0.83 0.84 0.83 79
2026-07-19 10:20:12 | INFO | M03-STUDENTS | --- Spring --- accuracy = 0.873
2026-07-19 10:20:12 | INFO | M03-STUDENTS | Per-class precision / recall / F1:
2026-07-19 10:20:12 | DEBUG | M03-STUDENTS |
precision recall f1-score support
fail 0.74 0.96 0.83 26
pass 0.98 0.83 0.90 53
accuracy 0.87 79
macro avg 0.86 0.90 0.87 79
weighted avg 0.90 0.87 0.88 79
2026-07-19 10:20:12 | INFO | M03-STUDENTS | Summary across quarters (fail = the at-risk class an alert is for):
2026-07-19 10:20:12 | DEBUG | M03-STUDENTS |
quarter accuracy fail_recall fail_precision fail_f1 pass_recall pass_precision pass_f1
Fall 0.658 0.15 0.44 0.23 0.91 0.69 0.78
Winter 0.835 0.69 0.78 0.73 0.91 0.86 0.88
Spring 0.873 0.96 0.74 0.83 0.83 0.98 0.90
2026-07-19 10:32:42 | DEBUG | M03-STUDENTS | depth= 1 train=0.820 test=0.797
2026-07-19 10:32:42 | DEBUG | M03-STUDENTS | depth= 2 train=0.820 test=0.785
2026-07-19 10:32:42 | DEBUG | M03-STUDENTS | depth= 3 train=0.858 test=0.835
2026-07-19 10:32:42 | DEBUG | M03-STUDENTS | depth= 4 train=0.883 test=0.772
2026-07-19 10:32:42 | DEBUG | M03-STUDENTS | depth= 5 train=0.896 test=0.823
2026-07-19 10:32:42 | DEBUG | M03-STUDENTS | depth= 6 train=0.911 test=0.810
2026-07-19 10:32:42 | DEBUG | M03-STUDENTS | depth= 7 train=0.927 test=0.861
2026-07-19 10:32:42 | DEBUG | M03-STUDENTS | depth= 8 train=0.949 test=0.835
2026-07-19 10:32:42 | DEBUG | M03-STUDENTS | depth= 9 train=0.965 test=0.848
2026-07-19 10:32:42 | DEBUG | M03-STUDENTS | depth=10 train=0.975 test=0.848
2026-07-19 10:32:42 | DEBUG | M03-STUDENTS | depth=11 train=0.981 test=0.835
2026-07-19 10:32:42 | DEBUG | M03-STUDENTS | depth=12 train=0.981 test=0.835
2026-07-19 11:02:30 | INFO | M03-STUDENTS | ========================
2026-07-19 11:02:30 | INFO | M03-STUDENTS | SUMMARY
2026-07-19 11:02:30 | INFO | M03-STUDENTS | ========================
2026-07-19 11:02:30 | INFO | M03-STUDENTS | Dataset: student-mat
2026-07-19 11:02:30 | INFO | M03-STUDENTS | Target: result (classification, pass/fail from G3)
2026-07-19 11:02:30 | INFO | M03-STUDENTS | Model: DecisionTreeClassifier(max_depth=3)
2026-07-19 11:02:30 | INFO | M03-STUDENTS | Prediction points (feature cases):
2026-07-19 11:02:30 | INFO | M03-STUDENTS | Fall (no grades): ['Medu', 'Fedu', 'studytime', 'failures', 'absences']
2026-07-19 11:02:30 | INFO | M03-STUDENTS | Winter (+G1): ['Medu', 'Fedu', 'studytime', 'failures', 'absences', 'G1']
2026-07-19 11:02:30 | INFO | M03-STUDENTS | Spring (+G1, G2): ['Medu', 'Fedu', 'studytime', 'failures', 'absences', 'G1', 'G2']
2026-07-19 11:02:30 | INFO | M03-STUDENTS | Scores by quarter:
2026-07-19 11:02:30 | DEBUG | M03-STUDENTS |
quarter accuracy fail_recall fail_precision fail_f1 pass_recall pass_precision pass_f1
Fall 0.658 0.15 0.44 0.23 0.91 0.69 0.78
Winter 0.835 0.69 0.78 0.73 0.91 0.86 0.88
Spring 0.873 0.96 0.74 0.83 0.83 0.98 0.90
2026-07-19 11:02:30 | INFO | M03-STUDENTS | ========================
2026-07-19 12:36:36 | INFO | ML | === RUN START ===
2026-07-19 12:36:36 | INFO | ML | project=ML
2026-07-19 12:36:36 | INFO | ML | repo_dir=ml-03-classification
2026-07-19 12:36:36 | INFO | ML | python=3.14.2
2026-07-19 12:36:36 | INFO | ML | os=Windows 11
2026-07-19 12:36:36 | INFO | ML | shell=powershell
2026-07-19 12:36:36 | INFO | ML | cwd=.
2026-07-19 12:36:36 | INFO | ML | github_actions=False
2026-07-19 13:18:54 | INFO | ML | === RUN START ===
2026-07-19 13:18:54 | INFO | ML | project=ML
2026-07-19 13:18:54 | INFO | ML | repo_dir=ml-03-classification
2026-07-19 13:18:54 | INFO | ML | python=3.14.2
2026-07-19 13:18:54 | INFO | ML | os=Windows 11
2026-07-19 13:18:54 | INFO | ML | shell=powershell
2026-07-19 13:18:54 | INFO | ML | cwd=.
2026-07-19 13:18:54 | INFO | ML | github_actions=False
2026-07-19 17:06:28 | INFO | ML | === RUN START ===
2026-07-19 17:06:28 | INFO | ML | project=ML
2026-07-19 17:06:28 | INFO | ML | repo_dir=ml-03-classification
2026-07-19 17:06:28 | INFO | ML | python=3.14.2
2026-07-19 17:06:28 | INFO | ML | os=Windows 11
2026-07-19 17:06:28 | INFO | ML | shell=powershell
2026-07-19 17:06:28 | INFO | ML | cwd=.
2026-07-19 17:06:28 | INFO | ML | github_actions=False