Topic: elbow-plot Goto Github
Some thing interesting about elbow-plot
Some thing interesting about elbow-plot
elbow-plot,Create an unsupervised Machine Learning Model to determine actively traded cryptocurrencies for new investment.
User: abednarz210
elbow-plot,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 history and on different ways they accrued or spent miles in the last year. The goal is to try to identify clusters of passengers that have similar characteristics for the purpose of targeting different segments for different types of mileage offers ID --Unique ID Balance--Number of miles eligible for award travel Qual_mile--Number of miles counted as qualifying for Topflight status cc1_miles -- Number of miles earned with freq. flyer credit card in the past 12 months: cc2_miles -- Number of miles earned with Rewards credit card in the past 12 months: cc3_miles -- Number of miles earned with Small Business credit card in the past 12 months: 1 = under 5,000 2 = 5,000 - 10,000 3 = 10,001 - 25,000 4 = 25,001 - 50,000 5 = over 50,000 Bonus_miles--Number of miles earned from non-flight bonus transactions in the past 12 months Bonus_trans--Number of non-flight bonus transactions in the past 12 months Flight_miles_12mo--Number of flight miles in the past 12 months Flight_trans_12--Number of flight transactions in the past 12 months Days_since_enrolled--Number of days since enrolled in flier program Award--whether that person had award flight (free flight) or not
User: abhik35
elbow-plot,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 has 3 clusters) PCA Implementation Checking with other Clustering Algorithms 1.Hierarchical Clustering 2.K-Means Clustering Build Cluster algorithm using K=3
User: abhik35
elbow-plot,Interactive knee point detection using kneed!
User: arvkevi
Home Page: https://arvkevi-kneed.streamlit.app/
elbow-plot,Clustering for Anuran Calls with 4 different families
User: aysenuryilmazz
elbow-plot,clustering of night time satellite images and depicting them by use of different colors
User: devxdebanjan
elbow-plot,This Project aims to cluster players on the basis of their performance on offensive side of court and give Winning Proportion of these groups in a team.
User: gauravjagtap-2611
elbow-plot,Credit engine majorly based on Unsupervised learning
User: hoturam
elbow-plot,Unsupervised learning algorithms to cluster students of a public school
User: imane-ayouni
elbow-plot,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.
User: jose-perth
elbow-plot,:chart_with_downwards_trend: Clustering of HTTP responses using k-means++ and the elbow method
User: manmolecular
elbow-plot,Used libraries and functions as follows:
User: patilsukanya
elbow-plot,Used libraries and functions as follows:
User: patilsukanya
elbow-plot,Clustering Project
User: priya-explorer
elbow-plot,Netflix Movies & TV Shows Clustering
User: rajivjha003
elbow-plot,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 clusters)
User: riteshopshrivastava
elbow-plot,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.
User: rochitasundar
elbow-plot,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 beginning who shows it has 3 clusters)df
User: rudraroy21
elbow-plot,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
User: s-chan11
elbow-plot,By aligning marketing efforts with customer preferences and desires, this approach promises to enhance market presence and drive substantial sales growth.
User: sadetosin
elbow-plot,Practice Code (R Codes)
User: saipavankumarb
elbow-plot,HELP International is 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 runs a lot of operational projects from time to time along with advocacy drives to raise awareness as well as for funding purposes. After the recent funding programmes, they have been able to raise around $ 10 million. Now the CEO of the NGO needs to decide how to use this money strategically and effectively. The significant issues that come while making this decision are mostly related to choosing the countries that are in the direst need of aid. And this is where you come in as a data analyst. Your job is to categorise the countries using some socio-economic and health factors that determine the overall development of the country. Then you need to suggest the countries which the CEO needs to focus on the most. The datasets containing those socio-economic factors and the corresponding data dictionary are provided below.
User: sakusuma
elbow-plot,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 how to use this money strategically and effectively. The significant issues that come while making this decision are mostly related to choosing the countries that are in the direst need of aid. The model is used to categorize the countries using some socio-economic and health factors that determine the overall development of the country.
User: smartnamdevoloper
elbow-plot,Segmenting customers of an audiobook platform and predicting their future purchase.
User: smh997
elbow-plot,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
User: srilakshmi-thota
elbow-plot,Machine learning utility functions and classes.
User: stefmolin
elbow-plot,The projects are a part of the internship by The Sparks Foundation
User: sumitkutty
elbow-plot,An investment advisory firm needs to segment stock offerings so they may offer their customers understandable investment options.
User: tpurcell0122github
elbow-plot,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 information on their mileage history and on different ways they accrued or spent miles in the last year. The goal is to try to identify clusters of passengers that have similar characteristics for the purpose of targeting different segments for different types of mileage offers.
User: vaitybharati
elbow-plot,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 have ignored at the begining who shows it has 3 clusters)
User: vaitybharati
elbow-plot,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 clusters)
User: vaitybharati
elbow-plot,Performing kmeans clustering and also providing elbow plot
User: vineeta12345
elbow-plot,Data Science - Capstone Project
User: vrayanoothala
elbow-plot,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
User: y656
elbow-plot,This is a Python implementation of k-means algorithm including elbow method and silhouette method for selecting optimal K
User: zillur-av
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