@ai-on-browser/data-analysis-models
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Data analysis model package without any dependencies
52 lines (51 loc) • 1.58 kB
TypeScript
/**
* Word2Vec
*/
export default class Word2Vec {
/**
* @param {'CBOW' | 'skip-gram'} method Method name
* @param {number} n Number of how many adjacent words to learn
* @param {number | string[]} wordsOrNumber Initial words or number of words
* @param {number} reduce_size Reduced dimension
* @param {string} optimizer Optimizer of the network
*/
constructor(method: "CBOW" | "skip-gram", n: number, wordsOrNumber: number | string[], reduce_size: number, optimizer: string);
_words: any[];
_wordsIdx: {};
_wordsNumber: number;
_n: number;
_method: "CBOW" | "skip-gram";
_layers: {
type: string;
name: string;
}[];
_model: NeuralNetwork;
_epoch: number;
/**
* Epoch
* @type {number}
*/
get epoch(): number;
/**
* Fit model.
* @param {string[]} words Training data
* @param {number} iteration Iteration count
* @param {number} rate Learning rate
* @param {number} batch Batch size
* @returns {number} Loss value
*/
fit(words: string[], iteration: number, rate: number, batch: number): number;
/**
* Returns predicted values.
* @param {string[]} x Sample data
* @returns {Array<Array<number>>} Predicted values
*/
predict(x: string[]): Array<Array<number>>;
/**
* Returns reduced values.
* @param {string[]} x Sample data
* @returns {Array<Array<number>>} Predicted values
*/
reduce(x: string[]): Array<Array<number>>;
}
import NeuralNetwork from './neuralnetwork.js';