I have build an lstm model to predict human activity recognition with dataset OPPORTUNITY. I did two experiment with different oder of processing as below,
split dataset to train,test and validation by selecting data from different person and different trial (follow a paper),then normalized with minmax scaler, reshape to (numberSample,timeSteps(windowlength),numberFeatures), training the model.
The dataset is highly imbalanced, I did not set class weight to the first one, but use class weight to the second one. The first one is working better than the second one, the second one is overfitting and shows worse accuracy. What is the reason? does the first one is responsible for Human activity recognition,since I disturb the original order of the sequence?.