@ai-on-browser/data-analysis-models
Version:
Data analysis model package without any dependencies
35 lines (34 loc) • 1.02 kB
TypeScript
/**
* Elastic net
*/
export default class ElasticNet {
/**
* @param {number} [lambda] Regularization strength
* @param {number} [alpha] Mixing parameter
* @param {'ISTA' | 'CD'} [method] Method name
*/
constructor(lambda?: number, alpha?: number, method?: 'ISTA' | 'CD');
_w: any;
_method: "ISTA" | "CD";
_lambda: number;
_alpha: number;
_soft_thresholding(x: any, l: any): void;
_calc_b0(x: any, y: any): void;
/**
* Fit model.
* @param {Array<Array<number>>} x Training data
* @param {Array<Array<number>>} y Target values
*/
fit(x: Array<Array<number>>, y: Array<Array<number>>): void;
/**
* Returns predicted values.
* @param {Array<Array<number>>} x Sample data
* @returns {Array<Array<number>>} Predicted values
*/
predict(x: Array<Array<number>>): Array<Array<number>>;
/**
* Returns importances of the features.
* @returns {number[]} Importances
*/
importance(): number[];
}