Struct XGBoostClassifier 

pub struct XGBoostClassifier {
    pub n_estimators: usize,
    pub learning_rate: f32,
    pub max_depth: usize,
    pub min_child_weight: f32,
    pub subsample: f32,
    pub colsample_bytree: f32,
    pub reg_lambda: f32,
    pub reg_alpha: f32,
    pub gamma: f32,
    /* private fields */
}

XGBoost-style Gradient Boosting

Features:

• Regularized learning objective (L1 and L2)
• Column (feature) subsampling
• Shrinkage (learning rate)
• Tree pruning with max_depth
• Histogram-based split finding

Fields

n_estimators: usize

learning_rate: f32

max_depth: usize

min_child_weight: f32

subsample: f32

colsample_bytree: f32

reg_lambda: f32

reg_alpha: f32

gamma: f32

Implementations

impl XGBoostClassifier

pub fn new(n_estimators: usize) -> Self

pub fn learning_rate(self, lr: f32) -> Self

pub fn max_depth(self, depth: usize) -> Self

pub fn subsample(self, ratio: f32) -> Self

pub fn colsample_bytree(self, ratio: f32) -> Self

pub fn reg_lambda(self, lambda: f32) -> Self

pub fn reg_alpha(self, alpha: f32) -> Self

pub fn fit(&mut self, x: &Tensor, y: &Tensor)

pub fn predict(&self, x: &Tensor) -> Tensor

pub fn predict_proba(&self, x: &Tensor) -> Tensor