I have a lot of features and many are correlated, so I performed dimensionality reduction. I then used these components in binary classification and got high accuracy. I also performed feature importance to see which of the features contributed the best to the separation of the 2 groups and found out that PC5 was the best to separate the groups. I looked at the feature loadings inside PC5 and saw that there are 2 features that loaded significantly higher than any other features on this component. Is it possible to say that those features contribute to the separation of the groups i was trying to classify more than other features? or would this not be the case?