Constructors
constructor
- new KernelizedPegasos(
rate: number,
kernel?:
| "gaussian"
| "polynomial"
| { name: "gaussian"; s?: number }
| { d?: number; name: "polynomial" }
| (arg0: number[], arg1: number[]) => number,
): KernelizedPegasos Parameters
- rate: number
Optional
kernel:
| "gaussian"
| "polynomial"
| { name: "gaussian"; s?: number }
| { d?: number; name: "polynomial" }
| (arg0: number[], arg1: number[]) => number
Properties
_a
_a: any[]
_itr
_itr: number
_k
_k: any[]
_kernel
_kernel: any
_r
_r: number
_t
_t: number
_x
_x: number[][]
_y
_y: (-1 | 1)[]
Methods
fit
- fit(): void
Returns void
init
- init(train_x: number[][], train_y: (-1 | 1)[]): void
Parameters
- train_x: number[][]
- train_y: (-1 | 1)[]
Returns void
predict
- predict(data: number[][]): (-1 | 1)[]
Returns (-1 | 1)[]
Predicted values
Kernelized Primal Estimated sub-GrAdientSOlver for SVM