Topic: silhouette-analysis Goto Github
Some thing interesting about silhouette-analysis
Some thing interesting about silhouette-analysis
silhouette-analysis,This project explores customer segmentation and market analysis in the context of online retail using an online retail dataset. By applying advanced analytics, we aim to uncover insights that can drive strategic decisions and enhance business performance.
User: abhroroy365
silhouette-analysis,Customer clustering using silhouette K-means and silhouette analysis on Python. Also using logistic regression on Python to predict top 30 customers.
User: arhapsari
silhouette-analysis,Learning Styles Segmentation using K-Prototypes
User: devanisdwi
silhouette-analysis,Unsupervised Learning - Using K Means algorithm to Cluster the customers.
User: iamjafar
silhouette-analysis,Data Mining - EDA, Feature Selection, Standardize, Remove Global Outliers, Normalize, Feature Extraction (with PCA), Clustering, Classification (baseline models and hyperparameter tuning with GridSearchCV).
User: josepaulosa
silhouette-analysis,Using the Elbow Method and Silhouette Analysis to find the optimal K in K-Means Clustering.
User: labrijisaad
silhouette-analysis,Creating predictive models to classify Trump's vote share and clustering counties based on demographics and economic variables. Report findings in PDF with detailed methodologies, model assessments, and R code for the project.
User: lefteris-souflas
silhouette-analysis,The project uses KMeans clustering on the Global Superstore dataset to categorize customers based on their buying habits, aiming to help retailers make better business decisions by tailoring their marketing strategies and improving their inventory management.
User: orestas41
Home Page: https://www.kaggle.com/code/orestasdulinskas/customer-segmentation
silhouette-analysis,Unsupervised machine learning
User: pierogio
silhouette-analysis,An analysis and approach to customer segmentation
User: vinayvirraj
silhouette-analysis,Implements K-means clustering for customer segmentation based on age, annual income, and spending score. The analysis aims to uncover distinct customer segments for targeted marketing and personalized customer experiences.
User: virajbhutada
silhouette-analysis,Utilized Python-based unsupervised machine learning algorithms, including K-Means and DBSCAN, to effectively segment the mall customer market.
User: zhenyuwangg
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