Machine Learning Essentials:Part 3
Unsupervised Learning
If there is no dependent variable or target variable in the dataset of interest meaning there is no information about what resulted from the observations in the respective units, it is unsupervised learning.
K-Means
The objective is to cluster observations based on their similarities. It can be thought of as a classification problem, where similar ones are grouped together but unlike a classification problem, the classes are not predefined in this example; similar ones are formed into a class without predefined categories.
How does it works?
Step 1: The number of clusters is determined.
Step 2: K random centers are selected.
Step 3: Distances to the K centers are calculated for each observation.
Step 4: Each observation is assigned to the nearest center or cluster.
Step 5: After the assignment process, new center calculations are made for the resulting clusters.
Step 6: This process is repeated for a specified number of iterations and the…
