Lesson 4 of 8Article18 min
Regression Models
Regression Models
When to use regression
- Forecasting sales or demand.
- Estimating prices, risk, or scores.
- Modeling relationships between numeric variables.
Linear regression baseline
Fit and evaluate linear regression
from sklearn.linear_model import LinearRegression
from sklearn.metrics import mean_absolute_error, r2_score
reg = LinearRegression()
reg.fit(X_train, y_train)
pred = reg.predict(X_test)
print("MAE:", mean_absolute_error(y_test, pred))
print("R2:", r2_score(y_test, pred))