In data mining association rule mining play vital role in finding associations between items in
a dataset by mining essential patterns in a large database. Standard association rules …

In this paper, discriminative associative classification is proposed as a new classification
technique based on class discriminative association rules (CDARs). These rules are defined …

Analyzing the influential factors of traffic accidents has been a hot topic in city management.
Most existing literature in this domain implemented linear based sensitivity analysis in …

Hierarchical Classification is a very important classification task for arranging data in a
hierarchical structure. Hierarchical arrangement of data is one of the best methods to …

Rule ranking is a crucial step in Associative Classification (AC), AC algorithms proposed
many ranking methods which aim to improve the accuracy of the classifier. In this paper we …

针对分类中如何有效利用负关联模式提高分类准确率, 提出了一种基于正负关联模式的分类算法
. 利用类Apriori 算法挖掘包含正项或/和负项且项与项之间互相关联的正负关联模式来产生分类 …

Classification using association is a data mining approach that integrates association rule
discovery and classification. Associative classification includes three main steps; rule …

Associative classification is the integration of classification and association rule discovery in
data mining. This approach often derives higher quality classifiers with reference to …

Associative classification integrates association rule and classification in data mining to
build classifiers that are highly accurate than that of traditional classification approaches …

In this study, we propose a new method to enhance the accuracy of Modified Multi-class
Classification based on Association Rule (MMCAR) classifier. We introduce a Partial Rule …