Treffer: A new inductive learning algorithm -- Separability-based inductive learning algorithm

Title:
A new inductive learning algorithm -- Separability-based inductive learning algorithm
Authors:
Wang, Zhengou, Lin, Yan
Publisher Information:
Science Press, Beijing
Subject Terms:
Memory and learning in psychology, decision tree, separability criterion, Decision theory, inductive learning algorithm
Document Type:
Fachzeitschrift Article
File Description:
application/xml
Access URL:
https://zbmath.org/409562
Accession Number:
edsair.c2b0b933574d..50069e320d728d1b3e1df9e4279701dc
Database:
OpenAIRE

Weitere Informationen

Summary: A new separability-based inductive learning algorithm is proposed. The algorithm is different from existing inductive learning algorithms. Starting directly from the separability of features for different classes, building a separability criterion, then forming a decision tree, the algorithm can classify multiclass concepts. The algorithm is intuitive, simple, and convenient for computation. Its effectiveness is illustrated by an example in this paper.