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Zenodo
2022
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| Online Access: | https://doi.org/10.5281/zenodo.18439850 |
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| _version_ | 1866901797672583168 |
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| author | Rishabh Sharma Dr. Shipra Arora |
| author_facet | Rishabh Sharma Dr. Shipra Arora |
| contents | As we know, Clustering analysis is a very important feature of machine learning. This process divides the data points on the basis of their characteristics. Similar data points come into the same group and unsimilar data points in different groups. So basically it makes a group of similar data points study further. This paper analysis K-means clustering algorithm by taking an example of cricket stats in which player capability is determined using their stats like wickets taken and run scored in their career. This capability can be used for the team selection purpose by selecting appropriate batsman, allrounders and bowler. |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_18439850 |
| institution | Zenodo |
| language | |
| publishDate | 2022 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Analysis of K-Means Clustering Algorithm Rishabh Sharma Dr. Shipra Arora Analysis K-means clustering pattern matching As we know, Clustering analysis is a very important feature of machine learning. This process divides the data points on the basis of their characteristics. Similar data points come into the same group and unsimilar data points in different groups. So basically it makes a group of similar data points study further. This paper analysis K-means clustering algorithm by taking an example of cricket stats in which player capability is determined using their stats like wickets taken and run scored in their career. This capability can be used for the team selection purpose by selecting appropriate batsman, allrounders and bowler. |
| title | Analysis of K-Means Clustering Algorithm |
| topic | Analysis K-means clustering pattern matching |
| url | https://doi.org/10.5281/zenodo.18439850 |