I’m trying to train a Multi-Output CNN-LSTM-Attention model for time series forecasting on a Solar dataset with multiple target variables. the outliers detection algorithms (IQR, zscore) identified 2000 data points as outliers but in reality these points are considered as normal picks that can occurs.
The dataset contains 3 features and target variables (irradiation, temperature, humidity) for time series forecasting.