Final Model Evaluation: Metrics
How do we evaluate a trained model using metrics?
Answer
Final evaluation of a trained model is done using the metric functions in the sklearn.metrics subpackage.
These functions take two parameters: y_test and y_pred.
from sklearn.metrics import mean_squared_error
from sklearn.linear_model import LinearRegression
model = LinearRegression()
model.fit(X_train, y_train)
y_pred = model.predict(X_test)
mse = mean_squared_error(y_test, y_pred)
print(mse)