diff options
Diffstat (limited to 'frontend/src/app/_elements/form-model')
-rw-r--r-- | frontend/src/app/_elements/form-model/form-model.component.html | 4 | ||||
-rw-r--r-- | frontend/src/app/_elements/form-model/form-model.component.ts | 15 |
2 files changed, 17 insertions, 2 deletions
diff --git a/frontend/src/app/_elements/form-model/form-model.component.html b/frontend/src/app/_elements/form-model/form-model.component.html index 8ec29a09..361e2545 100644 --- a/frontend/src/app/_elements/form-model/form-model.component.html +++ b/frontend/src/app/_elements/form-model/form-model.component.html @@ -11,7 +11,7 @@ <div class="ns-col"> <mat-form-field appearance="fill" class="mat-fix"> <mat-label>Tip problema</mat-label> - <mat-select [(ngModel)]="newModel.type"> + <mat-select [(ngModel)]="newModel.type" (selectionChange)="filterLossFunction()" disabled="true"> <mat-option *ngFor="let option of Object.keys(ProblemType); let optionName of Object.values(ProblemType)" [value]="option"> {{ optionName }} </mat-option> @@ -36,7 +36,7 @@ <mat-form-field appearance="fill" class="mat-fix"> <mat-label>Funkcija troška</mat-label> <mat-select [(ngModel)]="newModel.lossFunction"> - <mat-option *ngFor="let option of Object.keys(LossFunction); let optionName of Object.values(LossFunction)" [value]="option"> + <mat-option *ngFor="let option of Object.keys(lossFunction); let optionName of Object.values(lossFunction)" [value]="option"> {{ optionName }} </mat-option> </mat-select> diff --git a/frontend/src/app/_elements/form-model/form-model.component.ts b/frontend/src/app/_elements/form-model/form-model.component.ts index 71b374b0..82fa0e95 100644 --- a/frontend/src/app/_elements/form-model/form-model.component.ts +++ b/frontend/src/app/_elements/form-model/form-model.component.ts @@ -135,4 +135,19 @@ export class FormModelComponent implements AfterViewInit { updateTestSet(event: MatSliderChange) { this.testSetDistribution = event.value!; } + + filterLossFunction() { + if(this.newModel.type==ProblemType.Regression){ + this.lossFunction = LossFunctionRegression; + this.newModel.lossFunction=LossFunction.MeanSquaredError; + } + else if(this.newModel.type==ProblemType.BinaryClassification){ + this.lossFunction= LossFunctionBinaryClassification; + this.newModel.lossFunction=LossFunction.BinaryCrossEntropy; + } + else if(this.newModel.type==ProblemType.MultiClassification){ + this.lossFunction = LossFunctionMultiClassification; + this.newModel.lossFunction=LossFunction.SparseCategoricalCrossEntropy; + } + } } |