I am currently working on a machine learning project using Scikit-Learn, and I am having trouble with model evaluation and validation. I have split my data into training and testing sets using
train_test_split() function, and I have trained my model using a pipeline that includes preprocessing steps such as feature scaling and feature selection.
Here is the code I have so far:
However, I’m not sure if I’m doing the evaluation and validation correctly. Can someone help me understand the difference between model evaluation and validation in scikit-learn, and suggest any improvements to my code? Thank you!