I've done a clustering and I think that my results are too good to be trusted. Here is my pipeline:
- Inputs: a dataset of 208 images, distributed into 2 classes (99 and 109 images in each class).
- Extraction of 500 features for each image.
- Center (average 0) and reduce (std 1) each feature.
- Features selection with weka, using PCA+Ranker, which gave me a subset of 24 features.
- Clustering using 3 different algorithms: EM, K-means, X-means
The K-means and X-means provide perfect results (100% matching, according to the confusion matrix), and the EM has 80% accuracy.
I feel that my results are somewhere corrupted and consequently that I am doing something wrong.
- Is there something obviously wrong in my pipeline?
- Would you have any idea about how to confirm or contradict my results?