A Scripting Program for Clustering Unsupervised Learning using k-means method
clustering is the task of grouping a set of objects in such a way that objects in the same group (called a cluster) are more similar (in some sense) to each other than to those in other groups (clusters). It is a main task of exploratory data analysis, and a common technique for statistical data analysis, used in many fields, including pattern recognition, image analysis, information retrieval, bioinformatics, data compression, computer graphics and machine learning.
This Program will Preprocess The Input Dataset including replacing NaN Values and Categorized String Data into numerical so it can be measured for Clustering.
The Clustering Process will adapt k-means algorithm for finding cluster that apropriate for every two column of data.
to find the suitable amount of Cluster, this program also provide elbow Method Algorithm using Library and HeatMap Plotting for better understanding the Data Featured.
Use Python Environment or Google Collab
Data Read
Heatmap
Elbow Method
Result
