@ai-on-browser/data-analysis-models
Version:
Data analysis model package without any dependencies
34 lines (33 loc) • 927 B
TypeScript
/**
* Online gradient descent
*/
export default class OnlineGradientDescent {
/**
* @param {number} [c] Tuning parameter
* @param {'zero_one'} [loss] Loss type name
*/
constructor(c?: number, loss?: 'zero_one');
_c: number;
_w: any[];
_w0: number;
_t: number;
_loss: (t: any, y: any) => 0 | 1;
/**
* Update model parameters with one data.
* @param {number[]} x Training data
* @param {1 | -1} y Target value
*/
update(x: number[], y: 1 | -1): void;
/**
* Fit model parameters.
* @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 datas.
* @param {Array<Array<number>>} data Sample data
* @returns {(1 | -1)[]} Predicted values
*/
predict(data: Array<Array<number>>): (1 | -1)[];
}