Hello All,
I have a very large dataset. After computing the PCA I have selected its first and second Principal Components (PC).
In the attached file the scatter plot of these two PCs is illustrated.
I want to use these two PCs to classify two tasks.
Do you think is there any way or any transformation to change the feature space for separating these two PCs?
Thanks,
Hamed
The purpose of applying PCA is to extract the informative information of a big data into the first few components. For that PC are arranged according their higher variance. The scatter plot of the attached file denotes how the classes are separated for classification problems. If you wants more separable components then you can apply feature selection approaches after PCA transformation.
I believe you need more than 2 features to separate your classes. By the way, you can try Autoencoder instead of pca which might provides you better features.
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