# Define Top2 and Top3 Accuracy
from keras.metrics import categorical_accuracy, top_k_categorical_accuracy

def top_3_accuracy(y_true, y_pred):
    return top_k_categorical_accuracy(y_true, y_pred, k=3)

def top_2_accuracy(y_true, y_pred):
    return top_k_categorical_accuracy(y_true, y_pred, k=2)

# Compile the model
model.compile(Adam(lr=0.01), loss='categorical_crossentropy', metrics=[categorical_accuracy, top_2_accuracy, top_3_accuracy])

# Add weights to make the model more sensitive to melanoma
class_weights={
    0: 1.0,  # akiec
    1: 1.0,  # bcc
    2: 1.0,  # bkl
    3: 1.0,  # df
    4: 3.0,  # mel
    5: 1.0,  # nv
    6: 1.0,  # vasc
}