Computer Science
5 years ago

Revolutionizing Breast Cancer Detection: J48 Decision Tree Algorithm Leads with 84% Accuracy

Lecture notes on data engineering and communications technologies
Comparison of Decision Tree-Based Learning Algorithms Using Breast Cancer Data
M. S. Dawngliani, Nichith Chandrasekaran, R. Lalmawipuii, H. Thangkhanhau

Paper Summary

Related papers

Theme background image
Computer Science
2 years ago

New software revolutionizes teaching quality evaluation with ID3 decision tree algorithm!

Big Data Optimization
AI in Education
HR Analytics
Business, Management and Accounting
5 years ago

Revolutionizing Employee Performance Assessment with Simplified Decision Tree Algorithm

Big Data Analytics
HR Analytics
Neural Networks
1 view
Theme background image
Computer Science
6 years ago

ID3 Algorithm Measures Civil Servants' Performance, Enhancing Objective Assessment Process

Data Mining
Production Management
Multimedia Learning
1 view

The article compares six different decision tree-based learning algorithms using breast cancer data. The goal was to see which algorithm performed the best in predicting breast cancer outcomes. The researchers used a dataset from a cancer institute in India with 575 records and 24 attributes. They evaluated the algorithms using a technique called 10-fold cross validation. The results showed that the J48 decision tree had the highest accuracy at 84.21%, while the random forest tree had the lowest accuracy at 76.49%.