Class BayesianNetwork

constructor

• new BayesianNetwork(alpha: number): BayesianNetwork

  Parameters

  • alpha: number

    Equivalent sample size

  Returns BayesianNetwork

_alpha

_cand

_ess

_graph

_n

_score_method

_th

_bdeu

• _bdeu(
      x: any,
      graph?: any[] | null,
      cand?: any[] | null,
      exact?: boolean,
  ): number

  Parameters

  • x: any
  • Optionalgraph: any[] | null
  • Optionalcand: any[] | null
  • Optionalexact: boolean

  Returns number

_count

• _count(x: any, graph?: any[] | null, cand?: any[] | null): ArrayKeyMap[]

  Parameters

  • x: any
  • Optionalgraph: any[] | null
  • Optionalcand: any[] | null

  Returns ArrayKeyMap[]

_fitParameter

• _fitParameter(x: any): void

  Parameters

  • x: any

  Returns void

_fitStructure

• _fitStructure(x: any): void

  Parameters

  • x: any

  Returns void

_fitStructure_dp

• _fitStructure_dp(x: any): void

  Parameters

  • x: any

  Returns void

_logBDeu_appro

• _logBDeu_appro(x: any, graph?: any[] | null, cand?: any[] | null): number

  Parameters

  • x: any
  • Optionalgraph: any[] | null
  • Optionalcand: any[] | null

  Returns number

_logBDeu_exact

• _logBDeu_exact(x: any, graph?: any[] | null, cand?: any[] | null): number

  Parameters

  • x: any
  • Optionalgraph: any[] | null
  • Optionalcand: any[] | null

  Returns number

_score

• _score(x: any, graph?: any[] | null, cand?: any[] | null): number | undefined

  Parameters

  • x: any
  • Optionalgraph: any[] | null
  • Optionalcand: any[] | null

  Returns number | undefined

fit

• fit(x: any[][]): void

  Fit model.

  Parameters

  • x: any[][]

    Training data

  Returns void

probability

• probability(x: any[][]): number[]

  Returns probability values.

  Parameters

  • x: any[][]

    Sample data

  Returns number[]

  Predicted values