Stratified Cross Validator

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Fri May 20 2022 17:22:04 GMT+0000 (Coordinated Universal Time)

Saved by @biggusdickus #python

from sklearn.model_selection import StratifiedKFold
from sklearn.base import clone
skfolds = StratifiedKFold(n_splits=3, random_state=42)
for train_index, test_index in skfolds.split(X_train, y_train_5):
  clone_clf = clone(sgd_clf)
  X_train_folds = X_train[train_index]
  y_train_folds = y_train_5[train_index]
  X_test_fold = X_train[test_index]
  y_test_fold = y_train_5[test_index]
  clone_clf.fit(X_train_folds, y_train_folds)
  y_pred = clone_clf.predict(X_test_fold)
  n_correct = sum(y_pred == y_test_fold)
  print(n_correct / len(y_pred))



logreg=LogisticRegression()
stratifiedkf=StratifiedKFold(n_splits=5)
score=cross_val_score(logreg,X,Y,cv=stratifiedkf)
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