RandomizedSearchCV is a method provided by scikit-learn for hyperparameter tuning and model selection through cross-validation. It’s similar to GridSearchCV, but instead of exhaustively searching through all possible combinations of hyperparameters, it randomly samples a fixed number of hyperparameter settings from specified distributions. Here’s a basic overview of how RandomizedSearchCV works: Here’s a basic example of…
get_params() is a method provided by scikit-learn estimators (such as classifiers, regressors, transformers, etc.) that returns a dictionary of the estimator’s parameters. These parameters are the hyperparameters that define the behavior of the estimator and can be tuned during the model selection or hyperparameter optimization process. Here’s a simple example of how you might use…
SimpleImputer is a class in scikit-learn, a popular machine learning library in Python, used for handling missing values in datasets. It provides a simple strategy for imputing missing values, such as filling missing entries with the mean, median, most frequent value, or a constant. Here’s a basic example of how you might use SimpleImputer: This…
