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xgboost.predict
fn predict(ref self: Span<TreeNode<T>>, ref features: Span<T>, ref weights: Span<T>) -> T;
Predicts the target value for a set of features using the provided ensemble of decision trees and combining their results using given weights.
self: A reference to a span representing a ensemble of decision trees.features: A reference to a span representing the features for which the prediction is to be made.weights: A reference to a span representing the weights applied to the predictions from each tree.
The predicted target value.
Constrain input and output types to fixed point.
use orion::operators::ml::{FP16x16XGBoostRegressor, TreeRegressorTrait, TreeRegressor};
use orion::numbers::{FP16x16, FixedTrait};
fn xgboost_regressor_example(trees: Span<TreeRegressor<FP16x16>>) {
let mut features = array![
FixedTrait::new_unscaled(1, false),
FixedTrait::new_unscaled(2, false),
].span();
let mut weights = array![
FixedTrait::new_unscaled(0.5, false),
FixedTrait::new_unscaled(0.5, false)
].span();
FP16x16XGBoostRegressor::predict(ref trees, ref features, ref weights);
}
Last modified 1mo ago