clustering datascience kmeans clustering-validation elbow-method elbow-plot

• Updated Aug 26, 2019
• HTML

The project involves performing clustering analysis (K-Means, Hierarchical clustering, visualization post PCA) to segregate stocks based on similar characteristics or with minimum correlation. Having a diversified portfolio tends to yield higher returns and face lower risk by tempering potential losses when the market is down.

principal-component-analysis k-means-clustering agglomerative-clustering elbow-plot dendrogram sklearn-library standardscaler linkage-analysis silhouette-score scipy-library cophenetic-distance

• Updated Jan 20, 2022
• Jupyter Notebook

Machine learning utility functions and classes.

machine-learning pipeline pca confusion-matrix roc-curve residuals elbow-method elbow-plot roc-auc precision-recall-curve precision-recall adjusted-r-squared pr-curve scree-plot

• Updated Jan 14, 2023
• Python

Interactive knee point detection using kneed!

elbow-plot knee-point streamlit

• Updated Dec 20, 2021
• Python

📉 Clustering of HTTP responses using k-means++ and the elbow method

jupyter python3 data-analysis elbow-method elbow-plot k-means-plus-plus

• Updated Jul 21, 2021
• Jupyter Notebook

Function to find the optimal number of clusters for k-means analysis using the Elbow Method

r kmeans-clustering elbow-method elbow-plot kmeans-analysis elbow-point elbow-analysis

• Updated Dec 8, 2024
• R

Assignment-08-PCA-Data-Mining-Wine data. Perform Principal component analysis and perform clustering using first 3 principal component scores (both heirarchial and k mean clustering(scree plot or elbow curve) and obtain optimum number of clusters and check whether we have obtained same number of clusters with the original data (class column we h…

python scale sklearn pca-analysis decomposition scipy scatter-plot preprocessing data-mining-algorithms clustering-algorithm kmeans-clustering covariance-matrix hierarchical-clustering agglomerative-clustering elbow-plot dendrogram wcss variance-plot

• Updated Jul 3, 2021
• Jupyter Notebook

K-means Clustering algorithm is used to classify,experimenting with different values of K to find the elbow point in the plot error vs K

python machine-learning unsupervised-learning kmeans-clustering elbow-plot

• Updated Nov 2, 2019
• Python

This repository contains clustering techniques applied to minute weather data. It contains K-Means, Heirarchical Agglomerative clustering. I have applied various feature scaling techniques and explored the best one for our dataset

pandas-dataframe pca outlier-detection clustering-algorithm kmeans-clustering hierarchical-clustering unsupervised-machine-learning elbow-plot dendrogram truncated-svd minmaxscaling matplotlib-pyplot seaborn-plots kernelpca robust-scaling outliers-detection silhouette-score standard-scaler davies-bouldin

• Updated Jul 2, 2022
• Jupyter Notebook

This project demonstrates a Clustering Model using Python. An international humanitarian NGO that is committed to fighting poverty and providing the people of backward countries with basic amenities and relief during the time of disasters and natural calamities. It has been able to raise around $ 10 million. The model is needed to help decide ho…

sklearn outlier-detection kmeans-clustering linkage hierarchical-clustering bivariate-analysis elbow-plot hopkins univariate-analysis silhouette-score

• Updated Feb 14, 2021
• Jupyter Notebook

Used Unsupervised Machine Learning to create an analysis of cryptocurrencies on the trading market and how they could be grouped to create a classification system.

machine-learning pca elbow-plot

• Updated Nov 16, 2021
• Jupyter Notebook

The objective of this project is to analyze the customers of a bank, categorize them with K-Means and Hierarchical Clustering and evaluate their distinct characteristics

wss outlier-removal hierarchical-clustering sum-of-squared-error k-means-clustering elbow-method elbow-plot dendrogram linkage-analysis silhouette-score data-cleaning-and-preprocessing cluster-profiling

• Updated Jun 11, 2023
• Jupyter Notebook

Perform Principal component analysis and perform clustering using first 3 principal component scores (both heirarchial and k mean clustering(scree plot or elbow curve) and obtain optimum number of clusters and check whether we have obtained same number of clusters with the original data (class column we have ignored at the begining who shows it …

python scale clustering sklearn pca-analysis decomposition pca scipy scatter-plot preprocessing data-mining-algorithms kmeans-clustering covariance-matrix hierarchical-clustering agglomerative-clustering elbow-plot dendrogram wcss variance-plot

• Updated Jan 5, 2022
• Jupyter Notebook

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

python numpy sklearn pandas scatter-plot normalize clustering-algorithm kmeans-clustering sum-of-squares elbow-plot matplotlib-pyplot cluster-centers wcss standard-scaler

• Updated Jun 26, 2021
• Jupyter Notebook

Perform clustering (K means clustering) 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 histo…

python numpy sklearn pandas scatter-plot clustering-algorithm kmeans-clustering normalization elbow-plot matplotlib-pyplot cluster-centers wcss standard-scaler sumofasequence

• Updated Feb 13, 2022
• Jupyter Notebook

This project collects product data from Flipkart using web scraping techniques and performs data cleaning,exploratory data analysis,and machine learning modeling to extract meaningful business insights.The results are visualized using Power BI dashboards to analyze pricing trends,product ratings,reviewsand discount strategies in the e-commerce str.

python machine-learning sql machine-learning-algorithms jupyter-notebook selenium pickle webscraping machine-learning-models elbow-method beautifulsoup4 elbow-plot webscraping-data elbow-curves elbow-analysis

• Updated Mar 15, 2026
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Source code for examples of k-means and hierarchical clustering

gaussian-mixture-models kmeans simulated-data hierarchical-clustering elbow-plot

• Updated Jun 18, 2019
• Jupyter Notebook

Credit engine majorly based on Unsupervised learning

exploratory-data-analysis kmeans-clustering unsupervised-machine-learning elbow-plot creditengine

• Updated Jun 3, 2021
• Jupyter Notebook

Unsupervised-ML---K-Means-Clustering-Non-Hierarchical-Clustering-Univ. Use Elbow Graph to find optimum number of clusters (K value) from K values range. The K-means algorithm aims to choose centroids that minimise the inertia, or within-cluster sum-of-squares criterion WCSS. Plot K values range vs WCSS to get Elbow graph for choosing K (no. of c…

python numpy sklearn pandas scatter-plot normalize clustering-algorithm kmeans-clustering sum-of-squares kmeans-algorithm elbow-plot cluster-centroids matplotlib-pyplot wcss standard-scaler

• Updated Jun 27, 2021
• Jupyter Notebook

Segmenting customers of an audiobook platform and predicting their future purchase.

machine-learning clustering prediction pca-analysis classification kmeans-clustering svm-classifier random-forest-classifier customer-segmentation customer-relationship-management elbow-plot rfm-analysis xgbclassifier

• Updated Jan 28, 2022
• Jupyter Notebook