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dbscan-clustering

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In this notebook, i have tried to appy KMeans, Hierarchical and DBSCAN clustering along PCA. The dataset used is Mall_Customers. In DBSCAN, certain type of Heatmaps are used to find the Epsilon and min_samples value which have performed quite well in identifying the correct number of clusters.

  • Updated Apr 17, 2024
  • Jupyter Notebook

This assignment focuses on unsupervised learning techniques. The notebook explores clustering algorithms like K-Means and DBSCAN, applies dimensionality reduction using PCA, and evaluates clustering performance. It includes visualizations and analysis to understand how different methods group data and reduce complexity.

  • Updated May 28, 2024
  • Jupyter Notebook

Jupyter Notebooks exploring Machine Learning techniques -- regression, classification (K-nearest neighbour (KNN), Decision Trees, Logistic regression vs Linear regression, Support Vector Machine), clustering (k-means, Hierarchical Clustering, DBSCAN), sci-kit learn and SciPy -- and where it applies to the real world, including cancer detection, …

  • Updated May 21, 2020
  • Jupyter Notebook

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