Intelligent System – Week 5 (UNFINISHED)

In this post, is written my understanding of unsupervised learning through observation: Clustering. The clustering technique in this post will use K-means and Apriori algorithms.

Also, both the exercise and assignments of week five are uploaded here.

Assignment : Question -> Exercise for K-Means Answer -> K-MEANS(assignment)

Exercise       : K-MEANS -> K-MEANS(exercise) Apriori -> Exercise for Apriori

What is Unsupervised Learning?

Unsupervised learning is a category of machine learning in which, the machine is running an algorithm without any intervention of human interaction. Used to draw inferences from data sets consisting of input data without labeled responses.

The most common unsupervised learning method is cluster analysis, which is used for exploratory data analysis to find hidden patterns or grouping in data.

What is Clustering?

Clustering is a technique in attempt to group a set of similar entities together. In unsupervised machine learning, clustering is used to find the hidden similarities of each entities in the data and group them with each other based on the similarities found.