Multilayer neuron network

resources/js/pages/PerceptronViewer.vue

@@ -47,6 +47,7 @@ const props = defineProps<{
     minError: number;
     learningRate: number;
     maxIterations: number;
+    maxDisplayedWeights: number;
 }>();
 
 const selectedDatasetName = ref<string>('');
@@ -82,7 +83,9 @@ const cleanedDataset = computed<
     });
     return cleanedDataset;
 });
-const initializationMethod = ref<InitializationMethod>('zeros');
+const hiddenLayers = ref(3);
+const hiddenLayersNeurons = ref(3);
+const initializationMethod = ref<InitializationMethod>(props.type === 'multilayer' ? 'random' : 'zeros');
 
 console.log('Session ID:', props.sessionId);
 
@@ -145,7 +148,7 @@ function perceptroninitialization(data: any) {
         );
         return;
     }
-    activationFunction.value = data.activation_function;
+    activationFunction.value = data.activationFunction;
 }
 function getActivationFunction(type: string): (x: number) => number {
     switch (type) {
@@ -179,6 +182,8 @@ function resetTraining() {
                 :datasets="props.datasets"
                 :selectedDataset="selectedDatasetName"
                 :initializationMethod="initializationMethod"
+                :hidden-layers="hiddenLayers"
+                :hidden-layers-neurons="hiddenLayersNeurons"
                 :minError="props.minError"
                 :sessionId="props.sessionId"
                 :defaultLearningRate="props.learningRate"
@@ -203,6 +208,7 @@ function resetTraining() {
                     :iterations="iterations"
                     :trainingEnded="trainingEnded"
                     :trainingEndReason="trainingEndReason"
+                    :maxDisplayedWeights="props.maxDisplayedWeights"
                 />
             </div>
             <div class="sticky top-0 h-full w-full">
@@ -210,6 +216,7 @@ function resetTraining() {
                     <PerceptronDecisionGraph
                         :cleanedDataset="cleanedDataset"
                         :iterations="iterations"
+                        :is-regression="activationFunction === 'linear'"
                         :activation-function="
                             getActivationFunction(activationFunction)
                         "
@@ -218,6 +225,7 @@ function resetTraining() {
                 <div>
                     <PerceptronIterationsErrorsGraph
                         :iterations="iterations"
+                        :is-regression="activationFunction === 'linear'"
                         v-if="iterations.length > 0"
                     />
                 </div>