https://github.com/hxndev/k-means-on-iris-dataset
k-means clustering is a method of vector quantization, originally from signal processing, that aims to partition n observations into k clusters in which each observation belongs to the cluster with the nearest mean, serving as a prototype of the cluster.
https://github.com/hxndev/k-means-on-iris-dataset
code iris iris-dataset jupyter-notebook kmeans kmeans-algorithm kmeans-clustering kmeans-clustering-algorithm python
Last synced: 27 days ago
JSON representation
k-means clustering is a method of vector quantization, originally from signal processing, that aims to partition n observations into k clusters in which each observation belongs to the cluster with the nearest mean, serving as a prototype of the cluster.
- Host: GitHub
- URL: https://github.com/hxndev/k-means-on-iris-dataset
- Owner: HxnDev
- License: mit
- Created: 2021-08-04T07:56:03.000Z (over 3 years ago)
- Default Branch: main
- Last Pushed: 2021-08-04T07:57:09.000Z (over 3 years ago)
- Last Synced: 2023-03-04T18:38:10.718Z (about 2 years ago)
- Topics: code, iris, iris-dataset, jupyter-notebook, kmeans, kmeans-algorithm, kmeans-clustering, kmeans-clustering-algorithm, python
- Language: Jupyter Notebook
- Homepage:
- Size: 129 KB
- Stars: 3
- Watchers: 1
- Forks: 1
- Open Issues: 0