Cross Validation

Model Evaluation and Improvement

Learning Components

• Learning consists of representation, evaluation, and optimization.

Model Evaluation

• Using sklearn.datasets to create synthetic datasets.
• Splitting data into training and test sets using train_test_split.
• Instantiating a model (e.g., Logistic Regression) and fitting it to the training set.
• Evaluating the model on the test set using logreg.score(X_test, y_test).

Cross-Validation

• Definition: A statistical method for evaluating generalization performance.
• K-Fold Cross-Validation:
  • Data is divided into K