Page 101 - Data Science Algorithms in a Week

Random Forest

Now, given the partitions, let us create the branches and the child nodes.

We add a child node [Temperature=Cold] to the node [root]. This branch classifies four
feature(s): [['Cold', 'Breeze', 'Cloudy', 'No'], ['Cold', 'None', 'Sunny',
'Yes'], ['Cold', 'Breeze', 'Cloudy', 'No'], ['Cold', 'Breeze', 'Cloudy',
'No']].

We would like to add children to the node [Temperature=Cold].

We have the following variables available ['Wind', 'Sunshine']. As there are fewer of
them than the parameter m=4, we consider all of them. Of these, the variable with the
highest information gain is the variable Wind. Therefore, we will branch the node further
on this variable. We also remove this variable from the list of the available variables for the
children of the current node. Using the variable water Wind, we partition the data in the
current node as follows:

Partition for Wind=None: [['Cold', 'None', 'Sunny', 'Yes']]
Partition for Wind=Breeze: [['Cold', 'Breeze', 'Cloudy', 'No'],
['Cold', 'Breeze', 'Cloudy', 'No'], ['Cold', 'Breeze',
'Cloudy', 'No']]

Now, given the partitions, let us create the branches and the child nodes.
We add a child node [Wind=None] to the node [Temperature=Cold]. This branch
classifies one feature(s): [['Cold', 'None', 'Sunny', 'Yes']]

We would like to add children to the node [Wind=None].

We have the following variable available['Sunshine']. As there are fewer of them than
the parameter m=4, we consider all of them. Of these, the variable with the highest
information gain is the variable Sunshine. Therefore, we will branch the node further on
this variable. We also remove this variable from the list of the available variables for the
children of the current node. For the chosen variable Sunshine, all the remaining features
have the same value: Sunny. So, we end the branch with a leaf node. We add the leaf node
[Play=Yes].

We add a child node [Wind=Breeze] to the node [Temperature=Cold]. This branch
classifies three feature(s): [['Cold', 'Breeze', 'Cloudy', 'No'], ['Cold',
'Breeze', 'Cloudy', 'No'], ['Cold', 'Breeze', 'Cloudy', 'No']]

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