[Retracted] Implementing Machine Learning for Smart Farming to Forecast Farmers’ Interest in Hiring Equipment

Algorithm 1

Decision tree.

	INPUT: S, where S = set of classified instances
	OUTPUT: decision tree
	Require: S ≠ Φ, num_attributes >0
(1)	Procedure BUILD TREE
(2)	Repeat
(3)	maxGain < - 0
(4)	Split A < - null
(5)	e < - Entropy(Attributes)
(6)	For all attributes a in S do
(7)	Gain < - Information Gain (a, e)
(8)	If gain > maxGain then
(9)	maxGain < - gain
(10)	splitA < - a
(11)	End if
(12)	End for
(13)	Partition (S, split A)
(14)	until all partitions processed
(15)	End procedure