Data mining algorithm C4.5 decision trees generate
2016-08-23
0 0 0
no vote
Other
Earn points
&Decision tree algorithm is a kind of supervised learning, that is to say, a certain category and data set will be given in advance. Through learning, we can determine the class of the incoming data. Of course, many clustering algorithms are unsupervised learning, we will discuss later. As the name suggests, a decision tree is a tree like data structure, which can be either a multi tree or a binary tree. In fact, decision tree is constructed based on greedy strategy, and the optimal attribute is selected to split each time. The commonly used decision tree algorithms are ID3 and C4.5. In fact, these two algorithms are essentially the same, and they are found independently almost at the same time. ID3 the purpose of this algorithm is to reduce the depth of the tree. But the study of leaf number is ignored. C4.5 algorithm is improved on the basis of ID3. It is suitable for both classification and regression problems. It improves the missing value processing of prediction variables, pruning technology and derivation rules. Sometimes the decision tree will also have pruning considerations, mainly from the perspective of performance, noise and efficiency. &The application of the algorithm
c++
算法
源码
数据挖掘
生成
决策
Related Source Codes
Local Path Planning Algorithm - DWA Algorithm
0
0
no vote
Classic Interview Questions for Digital City Front
0
0
no vote
enDAQ-Shock-Data-Share-SRS-Blog
0
0
no vote
HDU-2553 N Queen Question
0
0
no vote
Calling chatGPT in a Windows application
0
0
no vote
No comment