PART 2 Excellent Good Fair Unsatisfactory For the provided BBC sports dataset: * Perform PCA * Plot the captured variance with respect to increasing latent dimensionality. * What is the minimum dimension that captures (a) at least 95% variance and (b) at least 98% variance? 5 marks Successfully completed all three tasks. 3 marks Successfully completed any two of the three tasks. 2 marks Successfully completed any one of the three tasks. 0 mark Failed to complete any given task.

Criteria 3: * Repeat K-means clustering with 5 clusters using a similarity measure other than Euclidean distance. * Evaluate the clustering performance over 50 random initializations of K-means using adjusted rand index and adjusted mutual information. * Report the clustering performance and compare it with the results obtained in step 2 5 marks Successfully completed all three tasks. 3 marks Successfully completed any two of the three tasks. 2 marks Successfully completed any one of the three tasks. 0 mark Failed to complete any given task.

Criteria 3: * Repeat K-means clustering with 5 clusters using a similarity measure other than Euclidean distance. * Evaluate the clustering performance over 50 random initializations of K-means using adjusted rand index and adjusted mutual information. * Report the clustering performance and compare it with the results obtained in step 2 5 marks Successfully completed all three tasks. 3 marks Successfully completed any two of the three tasks. 2 marks Successfully completed any one of the three tasks. 0 mark Failed to complete any given task.

Criteria 2: * Perform K-means clustering with 5 clusters using Euclidean distance as similarity measure. * Evaluate the clustering performance using adjusted rand index and adjusted mutual information. * Report the clustering performance averaged over 50 random initializations of K-means. 5 marks Successfully completed all three tasks. 3 marks Successfully completed any two of the three tasks. 2 marks Successfully completed only one of the three tasks. 0 mark Failed to complete any given task.

Criteria Excellent Good Fair Unsatisfactory Criteria 1: Reading files corresponding to the feature matrix, class labels and the term dictionary and store them in variables X, true Labels and terms using Python notebook. 5 marks Successfully read all files and stored in corresponding variables using Python notebook. 3 marks Partially achieved the goal by missing reading or storing one file or variable. 2 marks Only able to either reading files or creating variables in Python to store any value. 0 mark Fail to read and store using Python notebook.

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