Table of Contents

Mojo struct

PolyRegression

@memory_only
struct PolyRegression

A Gradient Descent based polynomial regression with mse as the loss function.

Aliases

  • MODEL_ID = 2

Fields

  • degree (Int): The maximal degree of the polynomial features.
  • lr (Float32): Learning rate.
  • n_iters (Int): The maximum number of iterations.
  • reg_alpha (Float32): Constant that multiplies the regularization term.
  • l1_ratio (Float32): The Elastic Net mixing parameter, with 0 <= l1_ratio <= 1. l1_ratio=0 corresponds to L2 penalty, l1_ratio=1 to L1.
  • tol (Float32): The stopping criterion based on loss.
  • batch_size (Int): Batch size, with batch_size=1 corresponds to SGD, 1 < batch_size < n_samples corresponds to Mini-Batch Gradient Descent.
  • random_state (Int): Used for shuffling the data.
  • weights (Matrix): Weights per feature.
  • bias (Float32): Bias term.

Implemented traits

AnyType, CV, Copyable, ImplicitlyDestructible, Movable

Methods

__init__

def __init__(out self, degree: Int = 2, learning_rate: Float32 = 0.01, n_iters: Int = 1000, reg_alpha: Float32 = 0, l1_ratio: Float32 = 0, tol: Float32 = 0, batch_size: Int = 0, random_state: Int = -1)

Args:

  • degree (Int)
  • learning_rate (Float32)
  • n_iters (Int)
  • reg_alpha (Float32)
  • l1_ratio (Float32)
  • tol (Float32)
  • batch_size (Int)
  • random_state (Int)
  • self (Self)

Returns:

Self

def __init__(out self, params: Dict[String, String])

Args:

  • params (Dict)
  • self (Self)

Returns:

Self

Raises:

fit

def fit(mut self, X: Matrix, y: Matrix)

Fit the model.

Args:

  • self (Self)
  • X (Matrix)
  • y (Matrix)

Raises:

predict

def predict(self, X: Matrix) -> Matrix

Predict regression values for X.

Args:

  • self (Self)
  • X (Matrix)

Returns:

Matrix: The predicted values.

Raises:

save

def save(self, path: String)

Save model data necessary for prediction to the specified path.

Args:

  • self (Self)
  • path (String)

Raises:

load

@staticmethod
def load(path: String) -> Self

Load a saved model from the specified path for prediction.

Args:

  • path (String)

Returns:

Self

Raises:

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