MinMax_Scaler_&_Split_Data

# Prepare data for the LSTM model
MinMax_Scaler = MinMaxScaler()
MinMax_feature_transform = MinMax_Scaler.fit_transform(Train_data, range(0, 1))
#MinMax_feature_transform = pd.DataFrame(MinMax_feature_transform, columns=Train_data.columns, index=Train_data.index)

# Split the data
timesplit= TimeSeriesSplit(n_splits=10)
for train_index, test_index in timesplit.split(MinMax_feature_transform):
        X_train, X_test = MinMax_feature_transform[:len(train_index)], MinMax_feature_transform[len(train_index): (len(train_index)+len(test_index))]
        y_train, y_test = Target_data[:len(train_index)].values.ravel(), Target_data[len(train_index): (len(train_index)+len(test_index))].values.ravel()