A cluster analysis leveraging the kmeans algorithm to determine which degrees are likely to yield which levels of income based on historical data.
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Updated
Feb 26, 2019 - Jupyter Notebook
A cluster analysis leveraging the kmeans algorithm to determine which degrees are likely to yield which levels of income based on historical data.
Segmenting with Mixed Type Data - A Case Study Using K-Medoids on Subscription Data
Comparing the Elbow Method and Silhouette Method for choosing the optimal number of clusters in K-Means algorithm
Analyze the data of batting figures of batsmen in ODI matches by Choosing strike rate and average as the two factors on which clustering the data
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
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
2019.07.08 2등 KCB 금융스타일 시각화 경진대회(KCB/DACON)
Identify major customer segments on a transnational data set that contains all the transactions occurring between 01/12/2010 and 09/12/2011 for a UK-based and registered non-store online retail.
Clustering of customer on the basis of their credit card details
K-means clustering, Evaluation methods of choosing k (Elbow Method, Silhouette analysis)
Clustering algorithms to segment clients of a distribution company
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.
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.
Using several clustering algorithm to segment an insurance company customers
An investment advisory firm needs to segment stock offerings so they may offer their customers understandable investment options.
Perform Principal component analysis and perform clustering using first 3 principal component scores both Heirarchial and K Means Clustering and obtain optimum number of clusters and check whether we have obtained same number of clusters with the original data.
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