deepbox/ml
Trees & Forests
Decision trees, random forests, extra trees, and tree export helpers for interpretable or high-variance tasks.
Trees
type ClassificationCriterion
export type ClassificationCriterion = "gini" | "entropy" | "log_loss";
ClassificationCriterion is a public type in deepbox/ml.
DecisionTreeClassifier
DecisionTreeClassifier is part of the deepbox/ml public API.
DecisionTreeRegressor
Decision Tree Regressor.
ExtraTreesClassifier
Extremely Randomized Trees Classifier.
ExtraTreesRegressor
Extremely Randomized Trees Regressor.
RandomForestClassifier
Random Forest Classifier.
RandomForestRegressor
Random Forest Regressor.
export_text
export declare function export_text(tree: DecisionTreeClassifier | DecisionTreeRegressor, options?: { featureNames?: readonly string[]; decimals?: number; }): string;
Build a text representation of a decision tree.
ml-tree.ts
import { DecisionTreeClassifier, ExtraTreesClassifier, RandomForestClassifier, export_text,} from "deepbox/ml";import { tensor } from "deepbox/ndarray";const X = tensor([[1, 2], [2, 1], [3, 3], [4, 4]]);const y = tensor([0, 0, 1, 1]);const tree = new DecisionTreeClassifier({ maxDepth: 2 }).fit(X, y);console.log(tree.predict(X).toString());console.log(export_text(tree));console.log(new RandomForestClassifier({ nEstimators: 20 }).fit(X, y).predict(X).toString());console.log(new ExtraTreesClassifier({ nEstimators: 20 }).fit(X, y).predict(X).toString());