Class GMeans

constructor

• new GMeans(): GMeans

  Returns GMeans

_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,
  ): { centroid: any; data: any[]; size: number }[]

  Parameters

  • model: any
  • datas: any

  Returns { centroid: any; data: any[]; size: number }[]

_distance

• _distance(a: any, b: any): number

  Parameters

  • a: any
  • b: any

  Returns number

_split_cluster

• _split_cluster(
      datas: any,
      k?: number,
  ): { centroid: any; data: any[]; size: number }[]

  Parameters

  • datas: any
  • Optionalk: number

  Returns { centroid: any; data: any[]; 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