Class XMeans

constructor

• new XMeans(): XMeans

• Returns XMeans

_centroids

_init_k

centroids

• get centroids(): number[][]

• Centroids

  Returns number[][]

size

• get size(): number

• Number of clusters.

  Returns number

_create_clusters

• _create_clusters(
      model: any,
      datas: any,
  ): {
      bic: number;
      centroid: any;
      cols: number;
      cov: Matrix;
      data: any[];
      llh: number;
      size: number;
  }[]

• Parameters

  • model: any
  • datas: any

  Returns {
      bic: number;
      centroid: any;
      cols: number;
      cov: Matrix;
      data: any[];
      llh: number;
      size: number;
  }[]

_distance

• _distance(a: any, b: any): number

• Parameters

  • a: any
  • b: any

  Returns number

_split_cluster

• _split_cluster(
      datas: any,
      k?: number,
  ): {
      bic: number;
      centroid: any;
      cols: number;
      cov: Matrix;
      data: any[];
      llh: number;
      size: number;
  }[]

• Parameters

  • datas: any
  • Optionalk: number

  Returns {
      bic: number;
      centroid: any;
      cols: number;
      cov: Matrix;
      data: any[];
      llh: number;
      size: number;
  }[]

clear

• clear(): void

• Clear all clusters.

  Returns void

fit

• fit(datas: number[][], iterations?: number): void

• Fit model.

  Parameters

  • datas: number[][]

    Training data
  • Optionaliterations: number

    Iteration count

  Returns void

predict

• predict(datas: number[][]): number[]

• Returns predicted categories.

  Parameters

  • datas: number[][]

    Sample data

  Returns number[]

  Predicted values