Struct LogisticRegressionBuilder 

pub struct LogisticRegressionBuilder { /* private fields */ }

Builder for creating LogisticRegression models with customizable configurations.

The LogisticRegressionBuilder provides methods to configure the properties of a LogisticRegression model before it is instantiated, following the Builder design pattern.

Fields

• n_features - The number of input features for the logistic regression model
• activation_fn - The activation function to use (default: Sigmoid)

Examples

use rust_ml::model::logistic_regression::LogisticRegression;
use rust_ml::core::activations::activation_functions::ActivationFn;
use rust_ml::builders::builder::Builder;

// Create a logistic regression model with 4 features and sigmoid activation
let model = LogisticRegression::builder()
    .n_features(4)
    .activation_function(ActivationFn::Sigmoid)
    .build()
    .unwrap();

Implementations

impl LogisticRegressionBuilder

pub fn new() -> Self

Creates a new LogisticRegressionBuilder with default parameter values.

The default configuration uses 1 feature and the Sigmoid activation function.

Returns

• Self - A new LogisticRegressionBuilder instance with default settings

pub fn n_features(self, n_features: usize) -> Self

Sets the number of input features for the logistic regression model.

Arguments

• n_features - The number of independent variables (features) in the input data

Returns

• Self - Builder instance with updated feature count for method chaining

pub fn activation_function(self, activation_function: ActivationFn) -> Self

Sets the activation function to use in the logistic regression model.

While sigmoid is the traditional activation function for logistic regression, other functions like ReLU or Tanh could be used for specific use cases.

Arguments

• activation_function - The activation function to use

Returns

• Self - Builder instance with updated activation function for method chaining

pub fn threshold(self, threshold: f64) -> Self

Sets the classification threshold for the logistic regression model.

Arguments

• threshold - The threshold value for classifying predictions (between 0 and 1)

Returns

• Self - Builder instance with updated threshold for method chaining

Trait Implementations

impl Builder<LogisticRegression, ArrayBase<OwnedRepr<f64>, Dim<[usize; 2]>>, ArrayBase<OwnedRepr<f64>, Dim<[usize; 1]>>> for LogisticRegressionBuilder

fn build(&self) -> Result<LogisticRegression, ModelError>

Builds and returns a new LogisticRegression model with the configured parameters.

Returns

• Result<LogisticRegression, ModelError> - A new LogisticRegression instance with the specified configuration, or an error if construction fails

impl Default for LogisticRegressionBuilder

fn default() -> Self

Creates a new LogisticRegressionBuilder with default parameter values.

The default configuration uses 1 feature and the Sigmoid activation function.

Returns

• Self - A new LogisticRegressionBuilder instance with default settings