The main goal of this project is to use various Clustering Methods for Bank Customer Segmentation.
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Updated
Aug 12, 2024 - Jupyter Notebook
The main goal of this project is to use various Clustering Methods for Bank Customer Segmentation.
Gaussian mixture models, k-means, mini-batch-kmeans and k-medoids clustering
[Under Review] Tackling Ambiguity from Perspective of Uncertainty Inference and Affinity Diversification for Weakly Supervised Semantic Segmentation
Integrated Analysis of Electric Power Consumption and Population Growth in the United Kingdom: Fitting, Forecasting, and Clustering Approaches
The code for "Label-efficient Segmentation via Affinity Propagation". [NeurIPS2023]
Music Recommendation System using Unsupervised Machine Learning Clustering Methods using K-Means, Fuzzy C Mean DBSCAN, Gaussian Mixture Model, BIRCH and Agglomerative Clustering
Cluster Face sorts images based on the faces in it.
Wine Classification using Machine learning algorithms
Cluster Visualization Tool
Undergraduate thesis for Bachelor in Computer Engineering
Comparing the clustering algorithms: affinity propagation and k-means and determining the execution time. DBCV Score was estimated.
Costumer segmentation was performed using the affinity propagation algorithm, PCA and autoencoders were used to optimize.
Sklearn, K-means Clustering, Hierarchical Clustering, DBSCAN, Mean Shift Clustering, Gaussian Mixture Models (GMM), Spectral Clustering, Affinity Propagation, OPTICS (Ordering Points to Identify the Clustering Structure), Birch (Balanced Iterative Reducing and Clustering using Hierarchies), marketing_campaign
Image Segmentation using Superpixels, Affinity Propagation and Kmeans Clustering
Finding Quality of wine using clustering principles
Predict traffic flow by affinity propagation clustering and LSTM
Scalable and concurrent programming implementation of Affinity Propagation clustering.
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