Solve this data lab using python

Outcome B: Apply data mining algorithms on datasets of variable size and

measurethe algorithm's performance.

Exercise:

Similar to Classification models you have applied and compared, now work on your selected

dataset by following below steps $($watch provided link$)$ for clustering models and comparison:

Step $1$: Import Needed Libraries

Step $2$: Read the experimental dataset

Step $($optional$)$: Shuffle the dataset to avoid bias

Step $3$: Perform Data Engineering $($Data Pre$-$processing$)$ Steps

Step $4$: Apply any two Clustering methods $($you can use the below methods$)$ using

the instructors here

a$)$ KMeans Clustering

b$)$ Hierarchical Clustering

c$)$ DBSCAN Clustering

Step $9$: Evaluate the performance of all the Clustering methods $($Graphically$)$ using

the instructions here

Step $10$: Select and Conclude the best performing clustering model for the given

dataset