@ai-on-browser/data-analysis-models
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Data analysis model package without any dependencies
46 lines (45 loc) • 1.29 kB
TypeScript
/**
* Bayesian Network
*/
export default class BayesianNetwork {
/**
* @param {number} alpha Equivalent sample size
*/
constructor(alpha: number);
_th: ArrayKeyMap[];
_graph: any[];
_alpha: number;
_ess: number;
_n: number;
_cand: any[];
_score_method: string;
/**
* Fit model.
* @param {Array<Array<*>>} x Training data
*/
fit(x: Array<Array<any>>): void;
_fitStructure(x: any): void;
_fitStructure_dp(x: any): void;
_score(x: any, graph?: any[], cand?: any[]): number;
_bdeu(x: any, graph?: any[], cand?: any[], exact?: boolean): number;
_logBDeu_exact(x: any, graph?: any[], cand?: any[]): number;
_logBDeu_appro(x: any, graph?: any[], cand?: any[]): number;
_fitParameter(x: any): void;
_count(x: any, graph?: any[], cand?: any[]): ArrayKeyMap[];
/**
* Returns probability values.
* @param {Array<Array<*>>} x Sample data
* @returns {number[]} Predicted values
*/
probability(x: Array<Array<any>>): number[];
}
declare class ArrayKeyMap {
_map: Map<any, any>;
get size(): number;
_getKey(key: any): any;
keys(): MapIterator<any>;
has(key: any): boolean;
get(key: any): any;
set(key: any, value: any): Map<any, any>;
}
export {};