Followed steps to classify wines:
- Preprocessed the dataset
- Used knn for classification
- Performed feature extraction
- Again, completed the classification process and compared the results
- Used linear dimensionality techniques such as PCA and LDA, and non-linear dimensionality techniques such as kernel PCA, Isomap, Locally Linear Embedding (LLE), Laplacian Eigenmap (sklearn.manifold.SpectralEmbedding) and t-SNE.
- Analyzed and compared performance of each.