Introduction to Model Evaluation in Machine Learning
What is Model Evaluation?
Model evaluation is the process of measuring how well a machine learning model performs on unseen data. Proper evaluation helps ensure that models generalize well and do not overfit the training dataset.
Why Model Evaluation is Important
- Measures model accuracy
- Identifies model weaknesses
- Improves predictive performance
- Helps select the best model
Example
python
from sklearn.metrics import accuracy_score
accuracy_score(y_test, y_pred)
Next Tutorial: Confusion Matrix
