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StratifiedShuffleSplit — scikit-learn 1.5.0 doc...
print ( f "Fold { i } :" ) ... print ( f " Train: index=...train_index } " ) ... print ( f " Test: index= { test_index }...scikit-learn.org/stable/modules/generated/sklearn.model_selection.StratifiedShuffleSplit.html -
model_evaluation.rst.txt
_precision_recall_f_measure_metrics: Precision, recall and F-measures...1_score>`_ (:math:`F_\beta` and :math:`F_1` measures) can be...scikit-learn.org/stable/_sources/modules/model_evaluation.rst.txt -
3.4. Metrics and scoring: quantifying the quali...
The F-measure ( \(F_\beta\) and \(F_1\) measures) can...score, also known as balanced F-score or F-measure. fbeta_score (y_true,...scikit-learn.org/dev/modules/model_evaluation.html -
GroupKFold — scikit-learn 1.5.0 documentation
print ( f "Fold { i } :" ) ... print ( f " Train: index=...train_index ] } " ) ... print ( f " Test: index= { test_index }...scikit-learn.org/stable/modules/generated/sklearn.model_selection.GroupKFold.html -
FeatureHasher — scikit-learn 1.5.0 documentation
'run' : 5 }] >>> f = h . transform ( D ) >>> f . toarray () array([[..."bird" ]] >>> f = h . transform ( raw_X ) >>> f . toarray () array([[...scikit-learn.org/stable/modules/generated/sklearn.feature_extraction.FeatureHasher.html -
1.16. Probability calibration — scikit-learn 1....
(y_i - \hat{f}_i)^2\] subject to \(\hat{f}_i \geq \hat{f}_j\) whenever...: \[p(y_i = 1 | f_i) = \frac{1}{1 + \exp(A f_i + B)} \,,\] where...scikit-learn.org/stable/modules/calibration.html -
bootstrap.js
nce[f]-d[f]-i.rects.popper[p],y=d[f]-i.rects.reference[f],w=...,k,M)),F=y===f?j:I,B={top:$.top-F.top+C.top,bottom:F.bottom-...scikit-learn.org/dev/_static/scripts/bootstrap.js -
GroupShuffleSplit — scikit-learn 1.5.0 document...
print ( f "Fold { i } :" ) ... print ( f " Train: index=...train_index ] } " ) ... print ( f " Test: index= { test_index }...scikit-learn.org/stable/modules/generated/sklearn.model_selection.GroupShuffleSplit.html -
SelectPercentile — scikit-learn 1.5.0 documenta...
See also f_classif ANOVA F-value between label/feature...for classification tasks. f_regression F-value between label/feature...scikit-learn.org/stable/modules/generated/sklearn.feature_selection.SelectPercentile.html -
1.17. Neural network models (supervised) — scik...
algorithm that learns a function \(f: R^m \rightarrow R^o\) by training...neuron MLP learns the function \(f(x) = W_2 g(W_1^T x + b_1) + b_2\)...scikit-learn.org/stable/modules/neural_networks_supervised.html