Difference between revisions of "...cluster"
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Given a set of data points, we can use a clustering algorithm to classify each data point into a specific group. In theory, data points that are in the same group should have similar properties and/or features, while data points in different groups should have highly dissimilar properties and/or features. Clustering is a method of unsupervised learning and is a common technique for statistical data analysis used in many fields. We can use clustering analysis to gain some valuable insights from our data by seeing what groups the data points fall into when we apply a clustering algorithm. [http://towardsdatascience.com/the-5-clustering-algorithms-data-scientists-need-to-know-a36d136ef68 The 5 Clustering Algorithms Data Scientists Need to Know] | Given a set of data points, we can use a clustering algorithm to classify each data point into a specific group. In theory, data points that are in the same group should have similar properties and/or features, while data points in different groups should have highly dissimilar properties and/or features. Clustering is a method of unsupervised learning and is a common technique for statistical data analysis used in many fields. We can use clustering analysis to gain some valuable insights from our data by seeing what groups the data points fall into when we apply a clustering algorithm. [http://towardsdatascience.com/the-5-clustering-algorithms-data-scientists-need-to-know-a36d136ef68 The 5 Clustering Algorithms Data Scientists Need to Know] | ||
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Revision as of 14:36, 2 June 2018
Given a set of data points, we can use a clustering algorithm to classify each data point into a specific group. In theory, data points that are in the same group should have similar properties and/or features, while data points in different groups should have highly dissimilar properties and/or features. Clustering is a method of unsupervised learning and is a common technique for statistical data analysis used in many fields. We can use clustering analysis to gain some valuable insights from our data by seeing what groups the data points fall into when we apply a clustering algorithm. The 5 Clustering Algorithms Data Scientists Need to Know
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If you know how many groups/classes there are...
- ...yes, then try the K-Means algorithm
- ...no, I do not know the amount of groups/classes
