My model was trained off of thousands of FENs which are simply chess positions and the move that was played as a response to that chess position. The model should output a predicted move in response to an FEN.

This is the code that I used to train the model:

def train(X, y):
    # Split the data into training and test sets
    X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.001, random_state=42)
    
    # Preprocess the data (you may need to implement FEN2ARRAY function for neural network input)
    X_train_processed = FEN2ARRAY(X_train)
    X_test_processed = FEN2ARRAY(X_test)
    
    # Encode the target variable (moves) for categorical classification
    label_encoder = LabelEncoder()
    label_encoder.fit(y_train)
    y_train_encoded = label_encoder.transform(y_train)
    y_test_encoded = label_encoder.transform(y_test)
    num_classes = len(label_encoder.classes_)
    
    # Convert target variable to one-hot encoded format
    y_train_categorical = to_categorical(y_train_encoded, num_classes=num_classes)
    y_test_categorical = to_categorical(y_test_encoded, num_classes=num_classes)
    
    # Define the neural network architecture
    model = Sequential()
    model.add(Dense(128, activation='relu', input_shape=(64,)))  # Adjust input_shape based on your input data
    model.add(Dense(64, activation='relu'))
    model.add(Dense(num_classes, activation='softmax'))  # Use softmax activation for multi-class classification
    
    # Compile the neural network model
    model.compile(optimizer='adam', loss='categorical_crossentropy', metrics=['accuracy'])
    
    # Train the neural network model
    model.fit(X_train_processed, y_train_categorical, epochs=10, batch_size=32, validation_data=(X_test_processed, y_test_categorical))
    
    return model

But when I output the prediction here:

prediction = model.predict(FEN2ARRAY("8/8/6p1/5k1p/4Rp1P/5P2/p5PK/r7 w - - 8 48"))
print(prediction)

I get this output:

1/1 [==============================] - 0s 83ms/step
[[9.8108569e-05 2.6935700e-04 9.9022780e-04 ... 2.1389520e-03
  1.9414679e-04 1.4036804e-03]]

How would I convert that output to a chess move?