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sandipanpaul21 / Clustering-in-Python

Star 116

Clustering methods in Machine Learning includes both theory and python code of each algorithm. Algorithms include K Mean, K Mode, Hierarchical, DB Scan and Gaussian Mixture Model GMM. Interview questions on clustering are also added in the end.

python clustering gaussian-mixture-models clustering-algorithm dbscan kmeans-clustering clustering-evaluation hierarchical-models hierarchical-clustering dbscan-clustering kmeans-algorithm clustering-coefficient clustering-validation clustering-methods dendogram dbscan-algorithm kmeans-analysis dbscan-clusters dbscan-clustering-algorithm k-mode
  • Updated Aug 7, 2024
  • Jupyter Notebook

shanuhalli / Assignment-Clustering

Star 3

Perform Clustering (Hierarchical, K Means Clustering and DBSCAN) for the airlines and crime data to obtain optimum number of clusters. Draw the inferences from the clusters obtained.

clustering exploratory-data-analysis dimensionality-reduction data-preprocessing dbscan-clustering dendogram k-means-clustering elbow-method min-max-scaler silhouette-score hirarchical-clustering standard-scaler assignment-07
  • Updated Dec 28, 2022
  • Jupyter Notebook

vaitybharati / Assignment-07-Clustering-Hierarchical-Airlines-

Star 3

Assignment-07-Clustering-Hierarchical-Airlines. Perform clustering (hierarchical) for the airlines data to obtain optimum number of clusters. Draw the inferences from the clusters obtained. Data Description: The file EastWestAirlinescontains information on passengers who belong to an airline’s frequent flier program. For each passenger the data …

python sklearn scipy scatter-plot clustering-algorithm normalization hierarchical-clustering dendogram agglomerative-clustering euclidean-distances ward-linkage
  • Updated Jun 19, 2021
  • Jupyter Notebook

shreyansh-2003 / Clustering-Analysis-KMeans-vs-Agglomerative-Clustering-for-Large-Datasets

Star 2

This repo explores KMeans and Agglomerative Clustering effectiveness in simplifying large datasets for ML. Goals include dataset download, finding optimal clusters via Elbow and Silhouette methods, comparing clustering techniques, validating optimal clusters, tuning hyperparameters. Detailed explanations and analysis are provided.

hyperparameter-optimization clustering-algorithm kmeans-clustering hierarchical-clustering dendogram elbow-method silhouette-score comparitive-study aglomerative-hierarchical-clustering
  • Updated May 28, 2023
  • Jupyter Notebook

yousefkotp / Network-Anomaly-Detection

Star 1

This project focuses on network anomaly detection due to the exponential growth of network traffic and the rise of various anomalies such as cyber attacks, network failures, and hardware malfunctions. This project implement clustering algorithms from scratch, including K-means, Spectral Clustering, Hierarchical Clustering, and DBSCAN

clustering k-means anomaly clustering-algorithm dbscan hierarchical-clustering density-based-clustering anomaly-detection dbscan-clustering unsupervised-machine-learning dendogram spectral-clustering k-means-implementation-in-python k-means-clustering unsupervised-clustering spectral-embedding anomaly-detection-algorithm db-scan anomaly-clustering network-anomaly
  • Updated Jun 11, 2023
  • Jupyter Notebook

Abhik35 / Assignment-Clustering-Hierarchical-Airlines

Star 1

Perform clustering (hierarchical) for the airlines data to obtain optimum number of clusters. Draw the inferences from the clusters obtained. Data Description: The file EastWestAirlinescontains information on passengers who belong to an airline’s frequent flier program. For each passenger the data include information on their mileage history and…

python sklearn a scipy scatter-plot clustering-algorithm normalization hierarchical-clustering dendogram agglomerative-clustering
  • Updated Feb 12, 2022
  • Jupyter Notebook

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