What are some effective techniques for model evaluation in machine learning?

What are some effective techniques for model evaluation in machine learning?

There are several techniques for model evaluation, including cross-validation, confusion matrix, and ROC curves.

Can you explain cross-validation?

Cross-validation is a technique where the dataset is split into multiple subsets to train and test the model, ensuring it generalizes well.

What is a confusion matrix?

A confusion matrix is a table used to evaluate the performance of a classification model by comparing predicted and actual values.

How do I interpret an ROC curve?

An ROC curve plots the true positive rate against the false positive rate, helping to assess the trade-off between sensitivity and specificity.