Hello! I was the pre-trained densenet161 for a car make and model classification problem. The accuracy is pretty good after 10 epoch, without fine tuning the learning rate.
However, I came across ‘XGBoost’ recently. From what I understood, we can use the trained CNN as feature extractor then do the training with XGBoost, that will handle the feature selection part.
I am a little bit confused.
- Will training with XGBoost also handle the classification part or do I need to set up a classifier to do that?
- I trained the model with
create_cnn, can I access the features with
- Do I fine tune the learning rate before extracting the features?
Can someone please help or direct me to some good resources?