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https://github.com/anezovic1/bike-share-prediction
https://github.com/anezovic1/bike-share-prediction
Last synced: about 2 months ago
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- Host: GitHub
- URL: https://github.com/anezovic1/bike-share-prediction
- Owner: anezovic1
- Created: 2024-02-02T12:44:19.000Z (11 months ago)
- Default Branch: main
- Last Pushed: 2024-05-14T15:00:43.000Z (8 months ago)
- Last Synced: 2024-07-12T02:03:42.155Z (6 months ago)
- Language: Jupyter Notebook
- Size: 2.64 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Project Description
The project's objective is to perform clustering on a selected dataset.
The group task involves data preprocessing and analysis, hypothesis formulation, and implementing prototype-based clustering. To determine the clustering tendency, Hopkins statistic was calculated, and for identifying the number of clusters, both the Elbow method and Silhouette method were employed.
For the individual task, the DBSCAN algorithm was chosen. This algorithm belongs to density-based methods. The purpose of density-based clustering is to locate regions of high density separated by regions of low density. The motivation for selecting this algorithm lies in its capability to determine the number of clusters automatically based on the data density, eliminating the need for a prior assumption about the number of clusters.
## Dataset
The dataset used for the project can be found at:
https://archive.ics.uci.edu/dataset/275/bike+sharing+dataset
## Results
The following plots illustrate the results of K-Means clustering and visual representations showcasing the outcomes of the DBSCAN algorithm. The DBSCAN algorithm was utilized three times with different parameter values. The third pass produced acceptable results, which are shown in the second image. Two clusters have been formed, but there are many outliers.
