Clusteval provides methods for unsupervised cluster validation

The Project focuses on Customers and Company, you have to analyze the sentiments of the reviews given by the customer in the data and made some useful conclusion in the form of Visualizations. Also, cluster the zomato restaurants into different segments. The data is visualized as it becomes easy to analyse data at instant.

I have clustered similar movies and TV Shows available on Netflix taking into account of attributes like Description, Cast, Director, Genre etc of a particular movie/show.

Customers RFM Clustering (Market Segmentation based on Behavioral Approach)

Comparing the Elbow Method and Silhouette Method for choosing the optimal number of clusters in K-Means algorithm

Customer Segmentation using R

A cluster analysis leveraging the kmeans algorithm to determine which degrees are likely to yield which levels of income based on historical data.

Clusterização dos dados presentes no dataset de câncer de mama, implementando os algoritmos K-means, algoritmo do cotovelo (elbow method) e da silhueta média (Silhouette).

This repository will be for our Geolog Silhouette Cluster Analysis

Customers RFM Clustering (Market Segmentation based on Behavioral Approach)

This Repository uses K-Means Clustering Algorithms , Silhouette Analysis and Elbow method in order to understand the customers like who can be easily converge [Target Customers] so that the sense can be given to marketing team and plan the strategy accordingly

For an UK based non-store online retail for which we need to cluster it's customers in to different groups so that we can run targeted campaign for each group

Using Spotify data to create a recommendation system for The Beatles

Implementing K-Means clustering for research about environmental awareness and environmental practices of Ecuadorian households regarding the enviroment

Customer personality analysis helps a business to modify its product based on its target customers from different types of customer segments.

An investment advisory firm needs to segment stock offerings so they may offer their customers understandable investment options.

This is a Python implementation of k-means algorithm including elbow method and silhouette method for selecting optimal K