svm.BaseSVM

BaseSVM class used by all parent SVM classes that are based on libsvm

Constructors

Methods

Constructors


constructor

new BaseSVM(options: `object`)

Defined in svm/classes.ts:75

Parameters:

ParamTypeDefaultDescription
options.cacheSizenumberCache size in MB
options.coef0numbercoef0 parameter for Polynomial and Sigmoid kernels
options.costnumberCost parameter, for C SVC, Epsilon SVR and NU SVR
options.degreenumberDegree of polynomial, test for polynomial kernel
options.epsilonnumberFor epsilon SVR
options.gammaGamma parameter of the RBF, Polynomial and Sigmoid kernels. Default value is 1/numfeatures
options.kernelKernelType of Kernel
options.nunumberFor NU SVC and NU SVR
options.probabilityEstimatesbooleanweather to train SVC/SVR model for probability estimates,
options.quietbooleanPrint info during training if false (aka verbose)
options.shrinkingbooleanUse shrinking euristics (faster)
options.tolerancenumberTolerance
options.weightSet weight for each possible class

Returns: BaseSVM

Methods


λ fit

Fit the model according to the given training data.

Defined in svm/classes.ts:101

Parameters:

ParamTypeDefaultDescription
Xnumber[][]
ynumber[]

Returns:

🤘 Promise<void>

λ fromJSON

Restores the model from a JSON checkpoint

Defined in svm/classes.ts:158

Parameters:

ParamTypeDefaultDescription
options.optionsanynull
options.svmanynull
options.typeanynull

Returns:

void

λ predict

Predict using the linear model

Defined in svm/classes.ts:125

Parameters:

ParamTypeDefaultDescription
Xnumber[][]

Returns:

number[]

λ predictOne

Predict the label of one sample.

Defined in svm/classes.ts:135

Parameters:

ParamTypeDefaultDescription
Xnumber[]

Returns:

number[]

λ toJSON

Saves the current SVM as a JSON object

Defined in svm/classes.ts:144

Returns:

ParamTypeDescription
svmanyundefined