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Mastering Python for Data Science by Samir Madhavan

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Summary

In this chapter, we explored the patterns in the census data and then understood how a decision tree was constructed and also built a decision tree model on the data given. You then learned the concept of ensemble models with the help of a random forest and improved the performance of prediction by using the random forest model.

In the next chapter, you'll learn clustering, which is basically grouping elements together that are similar to each other. We will use the k-means cluster for this.

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