#include "classifier.h"

float inputFeatures[3];
Eloquent::ML::Port::RandomForest randomForest;

void setup() {
    Serial.begin(115200);
}

void loop() {
    float inputValue1 = 0.9;
    float inputValue2 = 0.7;
    float inputValue3 = 0.5;
    float inputValue4 = 0.8;

    inputFeatures[0] = inputValue1;
    inputFeatures[1] = inputValue2;
    inputFeatures[2] = inputValue3;
    inputFeatures[3] = inputValue4;

    Serial.print("Input: ");
    Serial.println(String(inputValue1)+' | '+String(inputValue2)+' | '+String(inputValue3)+' | '+String(inputValue4));

    int prediction = randomForest.predict(inputFeatures);
    Serial.print("Prediction: ");
    Serial.println(prediction);

    const char* label = randomForest.predictLabel(inputFeatures);
    Serial.print("Label: ");
    Serial.println(label);

    performAction(prediction);

    delay(1000);
}

void performAction(int prediction) {
    switch (prediction) {
        case 0:
            Serial.println("Action for Setosa class");
            break;
        case 1:
            Serial.println("Action for Versicolor class");
            break;
        case 2:
            Serial.println("Action for Virginica class");
            break;
        default:
            Serial.println("Invalid prediction");
            break;
    }
}