Description
Two gene datasets (cho and iyer) can be found on Piazza. Please check the README file first for a short description of the two datasets.
Complete the following tasks:
- Implement five clustering algorithms to find clusters of genes that exhibit similar expression profiles: K-means, Hierarchical Agglomerative clustering with Min approach, density-based, mixture model, and spectral clustering. Compare these five methods and discuss their pros and cons.
For each of the above tasks, you are required to validate your clustering results using the following methods:
- Using external index (Rand Index and Jaccard Coefficient) and compare the clustering results from different clustering algorithms. The ground truth clusters are provided in the datasets.
- Visualize data sets and clustering results by Principal Component Analysis (PCA). You can use the PCA you implemented in Project 1 or use any existing implementation or package.
