A Python package for unsupervised mixed datatypes clustering
In this case study I will be doing Exploratory Data Analytics with the help of a case study on Bank marketing campaign.
My master thesis – It is about clustering of product data as provided by typical product information management systems.
Discover different segments of sessions which differ from each other by their navigational patterns before adding a product to the baskets. You are free to differentiate your segments based on category id or domain name of the products, if you feel necessary.Dimension reduction is also applied.
Developed a Customer Segmentation for a fictional insurance company by using, in one case, the combination of the K-means algorithm and the hierarchical clustering and in the other one K-Prototypes. Final clusters achieved crossing the results from both segmentations.
Predictive Modeling and Clustering Insights for Kickstarter Success
Teaching Clusteranalysis with generated Marathon-Shopper-Data
Data-Driven Strategies for Insurance Fraud Prevention and Vehicle Risk Assessment
Deploying clustering machine learning algorithms to segment survey respondents
Unsupervised learning analysis of a large depression dataset using mixed-data clustering, dimensionality reduction, and Bayesian Networks to explore socio-economic, lifestyle, and mental-health patterns.
A clustering ML project that performs a customer segmentation on a 2000-record dataset of various customers with different characteristics.
To associate your repository with the kprototypes topic, visit your repo's landing page and select "manage topics."