October 2018
Intermediate to advanced
214 pages
5h 31m
English
Content preview from Data Science Algorithms in a Week - Second Edition
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Random forest construction
We will construct a random forest that will consist of four random decision trees.
Construction of random decision tree number 0
We are given 10 features as input data. Of these, we choose all features randomly with their replacements for the construction of this random decision tree:
[['Warm', 'Strong', 'Cloudy', 'No'], ['Cold', 'Breeze', 'Cloudy', 'No'], ['Cold', 'None', 'Sunny', 'Yes'], ['Cold', 'Breeze', 'Cloudy', 'No'], ['Hot', 'Breeze', 'Cloudy', 'Yes'], ['Warm', 'Strong', 'Cloudy', 'No'], ['Hot', 'Breeze', 'Cloudy', 'Yes'], ['Hot', 'Breeze', 'Cloudy', 'Yes'], ['Cold', 'Breeze', 'Cloudy', 'No'], ['Warm', 'Breeze', 'Sunny', 'Yes']]
We start the construction with the root node to create the first node of the ...
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