Preprocess: LDA and Kernel PCA in Python

Principal component analysis (PCA) is an unsupervised linear transformation technique that is widely used across different fields, most prominently for dimensionality reduction. We talked about it here: https://charleshsliao.wordpress.com/2017/05/28/preprocess-pca-application-in-python/ We use the data from sklearn library, and the IDE is Python3. Most of the code comes from Sebastian Raschka's book: https://www.goodreads.com/book/show/25545994-python-machine-learning?ac=1&from_search=true

Clustering Application in Face Recognition in Python

We used face datasets for PCA application here: https://charleshsliao.wordpress.com/2017/05/28/preprocess-pca-application-in-python/ It also will be interesting to see how clustering algorithms assign images into different clusters and visualize them. We use the data from sklearn library(need to download face datasets separately), and the IDE is sublime text3. Most of the code comes from the book: https://www.goodreads.com/book/show/32439431-introduction-to-machine-learning-with-python?from_search=true

Clustering Algorithms Evaluation in Python

Sometimes we conduct clustering to match the clusters with the true labels of the dataset. Apparently this is one method to evaluate clustering results. We can also use other methods to complete the task with or without ground truth of the data. We use the data from sklearn library, and the IDE is sublime text3.… Continue reading Clustering Algorithms Evaluation in Python