Research on Monitoring Topping Time of Cotton Based on AdaBoost+Decision Tree
Algorithm 1
Bagging algorithm.
Input: training set , base learning algorithm , represents an input instance, n is the number of features, , represents the regression label, i = 1,2, …, N, N represents dataset size, number of training rounds for T.
Output: .
(1)
for t = 1, 2, …, T do
(2)
, represents the training set D is randomly sampled t times, and a total of m times are collected to obtain a sampling set containing m samples.
