Clustering is a technique for dividing data into clusters, with the same features in the same cluster.
In this chapter, we will cover the following topics:
- How to use the k-means clustering algorithm, using an example involving household incomes
- How to classify features by clustering them first with the features, along with the known classes, using an example of gender classification
- How to implement the k-means clustering algorithm in Python in the Implementation of k-means clustering algorithm section
- An example of house ownership and how to choose an appropriate number of clusters for your analysis
- How to use the example of house ownership to scale a given set of numerical data appropriately to improve the accuracy of classification by using a clustering algorithm
- An understanding of how different numbers of clusters alter the meaning...
