Class GMR

Gaussian mixture regression

Hierarchy (View Summary)

GMM
- GMR

Index

Constructors

Properties

_d _input_d _k _m _mx _my _p _s _sxx _sxy

Methods

_gaussian _init add clear fit predict probability

Constructors

constructor

new GMR(): GMR
Returns GMR
Inherited from GMM.constructor

Properties

_d

_d: any

_input_d

_input_d: number

_k

_k: number

_m

_m: any[]

_mx

_mx: any[]

_my

_my: any[]

_p

_p: any[]

_s

_s: any[]

_sxx

_sxx: any[]

_sxy

_sxy: any[]

Methods

_gaussian

_gaussian(x: any, m: any, s: any): number
Parameters
- x: any
- m: any
- s: any
Returns number
Inherited from GMM._gaussian
- Defined in lib/model/gmm.d.ts:31

_init

_init(datas: any): void
Parameters
- datas: any
Returns void
Inherited from GMM._init
- Defined in lib/model/gmm.d.ts:10

add

add(): void
Add a new cluster.

Returns void
Inherited from GMM.add
- Defined in lib/model/gmm.d.ts:14

clear

clear(): void
Clear all clusters.

Returns void
Inherited from GMM.clear
- Defined in lib/model/gmm.d.ts:18

fit

fit(x: number[][], y: number[][]): void
Fit model.
Parameters
- x: number[][]
  Training data
- y: number[][]
  Target values
Returns void
Overrides GMM.fit
- Defined in lib/model/gmm.d.ts:81

predict

predict(x: number[][]): number[][]
Returns predicted values.
Parameters
- x: number[][]
  Sample data
Returns number[][]
Predicted values
Overrides GMM.predict
- Defined in lib/model/gmm.d.ts:94

probability

probability(x: number[][], y: number[][]): number[][]
Returns probabilities.
Parameters
- x: number[][]
  Sample data
- y: number[][]
  Target values
Returns number[][]
Predicted values
Overrides GMM.probability
- Defined in lib/model/gmm.d.ts:88