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test(SVM): adding ONE_CLASS tests

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Lines changed: 39 additions & 0 deletions

Original file line number	Diff line number	Diff line change
`@@ -37,4 +37,43 @@ describe('SVM:asm', () => {`
`37`	`37`	`}`
`38`	`38`	`});`
`39`	`39`	`});`
	`40`	`+`
	`41`	`+test('should train using ONE_CLASS and RBF kernel on random values',()=>{`
	`42`	`+constsvm=newSVM({`
	`43`	`+kernel:KernelTypes.RBF,`
	`44`	`+type:SVMTypes.ONE_CLASS,`
	`45`	`+gamma:1,`
	`46`	`+cost:1,`
	`47`	`+nu:0.1,`
	`48`	`+quiet:true,`
	`49`	`+});`
	`50`	`+`
	`51`	`+constfeatures=[[0,0],[1,1],[1,0],[0,1]];`
	`52`	`+consttoPredict=[[0.5,0.5],[1.5,1]];`
	`53`	`+constexpected=[1,-1];`
	`54`	`+constlabels=[0,0,0,0];`
	`55`	`+`
	`56`	`+constexpectedModel={`
	`57`	`+model:null,`
	`58`	`+options:{`
	`59`	`+kernel:'RBF',`
	`60`	`+type:'ONE_CLASS',`
	`61`	`+gamma:1,`
	`62`	`+cost:1,`
	`63`	`+nu:0.1,`
	`64`	`+quiet:true,`
	`65`	`+},`
	`66`	`+loaded:false,`
	`67`	`+};`
	`68`	`+`
	`69`	`+expect(svm.toJSON()).toMatchObject(expectedModel);`
	`70`	`+`
	`71`	`+svm.loadASM().then((loadedSVM)=>{`
	`72`	`+loadedSVM.train({samples:features, labels});`
	`73`	`+for(leti=0;i<toPredict.length;i++){`
	`74`	`+constpred=loadedSVM.predictOne({sample:toPredict[i]});`
	`75`	`+expect(pred).toBe(expected[i]);`
	`76`	`+}`
	`77`	`+});`
	`78`	`+});`
`40`	`79`	`});`

Lines changed: 39 additions & 0 deletions

Original file line number	Diff line number	Diff line change
`@@ -37,4 +37,43 @@ describe('SVM:wasm', () => {`
`37`	`37`	`}`
`38`	`38`	`});`
`39`	`39`	`});`
	`40`	`+`
	`41`	`+test('should train using ONE_CLASS and RBF kernel on random values',()=>{`
	`42`	`+constsvm=newSVM({`
	`43`	`+kernel:KernelTypes.RBF,`
	`44`	`+type:SVMTypes.ONE_CLASS,`
	`45`	`+gamma:1,`
	`46`	`+cost:1,`
	`47`	`+nu:0.1,`
	`48`	`+quiet:true,`
	`49`	`+});`
	`50`	`+`
	`51`	`+constfeatures=[[0,0],[1,1],[1,0],[0,1]];`
	`52`	`+consttoPredict=[[0.5,0.5],[1.5,1]];`
	`53`	`+constexpected=[1,-1];`
	`54`	`+constlabels=[0,0,0,0];`
	`55`	`+`
	`56`	`+constexpectedModel={`
	`57`	`+model:null,`
	`58`	`+options:{`
	`59`	`+kernel:'RBF',`
	`60`	`+type:'ONE_CLASS',`
	`61`	`+gamma:1,`
	`62`	`+cost:1,`
	`63`	`+nu:0.1,`
	`64`	`+quiet:true,`
	`65`	`+},`
	`66`	`+loaded:false,`
	`67`	`+};`
	`68`	`+`
	`69`	`+expect(svm.toJSON()).toMatchObject(expectedModel);`
	`70`	`+`
	`71`	`+svm.loadWASM().then((loadedSVM)=>{`
	`72`	`+loadedSVM.train({samples:features, labels});`
	`73`	`+for(leti=0;i<toPredict.length;i++){`
	`74`	`+constpred=loadedSVM.predictOne({sample:toPredict[i]});`
	`75`	`+expect(pred).toBe(expected[i]);`
	`76`	`+}`
	`77`	`+});`
	`78`	`+});`
`40`	`79`	`});`

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