项目作者: shayansoh

项目描述 :
Comparison of various distance metrics used in clustering techniques for unsupervised learning
高级语言: Jupyter Notebook
项目地址: git://github.com/shayansoh/Distance-Metrics-in-Clustering.git
创建时间: 2020-11-09T17:48:25Z
项目社区:https://github.com/shayansoh/Distance-Metrics-in-Clustering

开源协议:MIT License

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Distance Metric Comparison in Clustering for Unsupervised Learning

In this project, we will explore the importance of various metrics that are used for measuring distances in machine learning. There are many ways of computing the distances between points including euclidean, cityblock, minkowski, hamming, cosine and jaccard.

We will be exploring a cars dataset to look into how K-Means clustering and Agglomerative Hierarchical clustering is impacted by using euclidean or cosine distance.