如何将SelectKBest的输出传递给cross_val_score函数？

Question

I have the following code here:

I am trying to retrieve the 20 best features from my dataset and then test the cross validated score with the Random Forest Classifier however once I've performed SelectKBest I recieve an output: X_train_selected and X_test_selected and it's not immediately obvious to me how I pass this to the cross val score function.

Answer 1

You don't need to separate train and test data for cross_val_score. The function itself just takes care of it. When passing the features set, you need to pass the complete feature set, not X_train and X-test

First seperate the target variable

target = df['result']

Then run the selectKbest and get the column names like you did, but this time instead of splitting the X into train and test, just pass them as single data set like this

X = clean_df[colnames_selected]

Then pass the X and target to cross_val_score

scores = cross_val_score(forest, X, target, cv=10)
print("Reduced features: mean of the scores: {:.2f}".format(scores.mean()))

The whole point of the function is to perform cross validation on the dataset and return the scores using the estimators provided.

You can also use pipelines to make this whole process more easier in go like this example .