ID3 Algorithm Research in Data Mining. Apply ID3 Algorithm in Some Machine Learning Problems, Making Decisions. Install Problems in Python Programming Language

EasyChair Preprint 10452

Abstract

Data mining (DM) can be said to be a young but promising field of Information Technology. Data mining is understood as a statistical computational process to find determinants in large data sets. This is a field that deals with statistics, machine learning, database, etc. Decision trees are like strategists making timely and quick decisions based on decision tree analysis. In the industrial age 4.0, whoever has information and can make decisions early and in time will succeed. Nowadays, decision tree data mining techniques are widely used in machine learning and big data processing. The key and deep meaning in decision tree construction algorithms is the calculation of "the degree of discrimination of an attribute from the decision attribute in the data." In information theory, it has been shown that the This is also the foundation to build the ID3 algorithm. In this article, I would like to mention again the formula about the relationship between entropy and discriminant degree of an attribute. computation in data mining, ID3 algorithm and algorithm implementation through a few practical examples.

Keyphrases: Cây quyết định, Khai phá dữ liệu, học máy, lập trình Python

@booklet{EasyChair:10452,
  author    = {Tran Thi Gia},
  title     = {ID3 Algorithm Research in Data Mining. Apply ID3 Algorithm in Some Machine Learning Problems, Making Decisions. Install Problems in Python Programming Language},
  howpublished = {EasyChair Preprint 10452},
  year      = {EasyChair, 2023}}