@ai-on-browser/data-analysis-models
Version:
Data analysis model package without any dependencies
78 lines (77 loc) • 1.84 kB
TypeScript
/**
* Perceptron
*/
export class Perceptron {
/**
* @param {number} rate Learning rate
*/
constructor(rate: number);
_r: number;
_a: any[];
_b: number;
/**
* Fit model.
* @param {Array<Array<number>>} x Training data
* @param {Array<1 | -1>} y Target values
*/
fit(x: Array<Array<number>>, y: Array<1 | -1>): void;
/**
* Returns predicted values.
* @param {Array<Array<number>>} data Sample data
* @returns {(1 | -1)[]} Predicted values
*/
predict(data: Array<Array<number>>): (1 | -1)[];
}
/**
* Averaged perceptron
*/
export class AveragedPerceptron {
/**
* @param {number} rate Learning rate
*/
constructor(rate: number);
_r: number;
_epoch: number;
_a: any[];
_atotal: any[];
_b: number;
_btotal: number;
/**
* Fit model.
* @param {Array<Array<number>>} x Training data
* @param {Array<1 | -1>} y Target values
*/
fit(x: Array<Array<number>>, y: Array<1 | -1>): void;
/**
* Returns predicted values.
* @param {Array<Array<number>>} data Sample data
* @returns {(1 | -1)[]} Predicted values
*/
predict(data: Array<Array<number>>): (1 | -1)[];
}
/**
* Multiclass perceptron
*/
export class MulticlassPerceptron {
/**
* @param {number} rate Learning rate
*/
constructor(rate: number);
_r: number;
_c: any[];
_epoch: number;
_a: any[];
_b: any[];
/**
* Fit model.
* @param {Array<Array<number>>} x Training data
* @param {*[]} y Target values
*/
fit(x: Array<Array<number>>, y: any[]): void;
/**
* Returns predicted values.
* @param {Array<Array<number>>} data Sample data
* @returns {*[]} Predicted values
*/
predict(data: Array<Array<number>>): any[];
}