Mall Customer Segmentation using K-Means Algorithm

This project demonstrates the use of K-Means clustering on two popular datasets: the Iris dataset and the Mall Customers dataset. The goal is to visualize the clustering process and group similar data points, showcasing the practical application of K-Means in real-world data segmentation.

This project applies unsupervised machine learning techniques to segment customers of a mall

This project aims to perform customer segmentation on a Mall customer dataset using the K-Means clustering algorithm. The goal of this project is to cluster the customers based on their purchasing behavior and demographic characteristics.

This project applies Hierarchical Clustering to segment customers based on their Annual Income and Spending Score. It uses dendrograms to determine the number of clusters and applies Agglomerative Clustering for grouping.

Customer segmentation is a crucial task in marketing analytics that helps businesses understand customer behavior and target them effectively. This project applies K-Means Clustering, an unsupervised machine learning algorithm, to segment mall customers into distinct groups based on their purchasing behavior.

Mall customer segmentation using K Means Clustering

Implementation of the core concept/algorithm using K-means Clustering.

To discover distinct groups of customers from a mall dataset based on features like age, annual income, and spending behavior.

Repository for various clustering projects including mall customer segmentation and more. Explore data analysis and clustering techniques

A mall customer segmentation machine learning model categorizes customers based on their behaviors and preferences, enabling businesses to tailor marketing strategies and optimize operations for improved customer satisfaction and business growth.

客户购物偏好分析（Mall Customer Segmentation） 数据集链接：Mall Customer Segmentation Data 分析目标： 分析年龄、收入与消费评分的分布。 使用K-Means对客户聚类。 可视化不同群体特征（如雷达图）。

Customer Segmentation using KMeans algorithm on Mall_Customers Dataset.

This project performs customer segmentation using the Mall Customer dataset. The goal is to cluster customers based on their Annual Income and Spending Score to identify meaningful segments and gain business insights.

mall cusomer segmenation using usupervised ML (dbscan, k-cmean, fcmean)

Mall Customer Segmentation