https://github.com/moindalvs/assignment_crime_data_clustering
Content This data set contains statistics, in arrests per 100,000 residents for assault, murder, and rape in each of the 50 US states in 1973. Also given is the percent of the population living in urban areas.This is a systematic approach for identifying and analyzing patterns and trends in crime using USArrest dataset.
https://github.com/moindalvs/assignment_crime_data_clustering
clustering-algorithm data-science dbscan-clustering epsilon hierarchical-clustering kmeans-clustering
Last synced: 9 months ago
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Content This data set contains statistics, in arrests per 100,000 residents for assault, murder, and rape in each of the 50 US states in 1973. Also given is the percent of the population living in urban areas.This is a systematic approach for identifying and analyzing patterns and trends in crime using USArrest dataset.
- Host: GitHub
- URL: https://github.com/moindalvs/assignment_crime_data_clustering
- Owner: MoinDalvs
- Created: 2022-05-02T06:59:02.000Z (over 3 years ago)
- Default Branch: main
- Last Pushed: 2022-05-02T07:13:32.000Z (over 3 years ago)
- Last Synced: 2025-01-18T00:44:50.978Z (10 months ago)
- Topics: clustering-algorithm, data-science, dbscan-clustering, epsilon, hierarchical-clustering, kmeans-clustering
- Language: Jupyter Notebook
- Homepage:
- Size: 4.63 MB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
## 1. Content
+ This data set contains statistics, in arrests per 100,000 residents for assault, murder, and rape in each of the 50 US states in 1973. Also given is the percent of the population living in urban areas.This is a systematic approach for identifying and analyzing patterns and trends in crime using USArrest dataset.
A data frame with 50 observations on 4 variables.
+ Murder is numeric and Murder arrests (per 100,000)
+ Assault is numeric and Assault arrests (per 100,000)
+ UrbanPop is numeric and UrbanPop arrests (per 100,000)
+ Rape is numeric and Rape arrests (per 100,000)
# Problem Statement
## Perform Clustering(Hierarchical, Kmeans & DBSCAN) for the crime data and identify the number of clusters formed and draw inferences.
### Draw the inferences from the clusters obtained.