Regression Algorithms

Linear Regression

Predict continuous values using supervised learning. Evaluate with R², MSE, MAE, and RMSE metrics.

Train Linear Regression

-- Train linear regression model
SELECT train_linear_regression(
    'linear_train',      -- Training table
    'features',          -- Feature column
    'amount'             -- Target column (continuous)
) AS coefficients;

Evaluate Model

-- Evaluate on test data
SELECT evaluate_linear_regression(
    'linear_test',       -- Test table
    'features',          -- Feature column
    'amount',            -- Target column
    :coefficients        -- Model coefficients
) AS test_metrics;

-- Returns array: [R², MSE, MAE, RMSE]

Ridge Regression

Linear regression with L2 regularization to prevent overfitting.

SELECT train_ridge_regression(
    'training_data',
    'features',
    'target',
    0.1  -- Alpha (regularization strength)
) AS coefficients;

Lasso Regression

Linear regression with L1 regularization for feature selection.

SELECT train_lasso_regression(
    'training_data',
    'features',
    'target',
    0.1  -- Alpha (regularization strength)
) AS coefficients;

Next Steps

• RAG Pipeline - Build RAG applications
• Hyperparameter Tuning - Optimize model parameters
• Model Management - Deploy models