Logistic Regression (aolearn.logistic)

fit_logistic(X, y, learningRate, numIterations)

Trains a logistic regression model using gradient descent.

Parameters:

• X (table): Training features.
• y (table): Training labels (0 or 1).
• learningRate (number): Learning rate.
• numIterations (number): Number of iterations.

Returns:

• table, number: A table containing the learned weights and the learned bias.

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predict_logistic_sigmoid(weights, bias, features)

Predicts probabilities using a fitted logistic regression model (producing a sigmoid output).

Parameters:

• weights (table): Learned weights from fit_logistic.
• bias (number): Learned bias from fit_logistic.
• features (table): Features for a single data point.

Returns:

• number: Predicted probability (a value between 0 and 1).