Add to ORKGAbstract. We present ELEM2, a new method for inducing classification rules from a set of examples. The method employs several new strategies in the induction and classification processes to improve the predictive performance of induced rules. In particular, a new heuristic function for evaluating attribute-value pairs is proposed. The function is defined to reflect the degree of relevance of an attribute-value pair to a target con-cept and leads to selection of the most relevant pairs for formulating rules. Another feature of ELEM2 is that it handles inconsistent training data by defining an unlearnable region of a concept based on the prob-ability distribution of that concept in the training data. To further deal with imperfect data, ELEM2...
Generating classification rules from data often leads to large sets of rules that need to be pruned....
Association rule-based classifiers have recently emerged as competitive classification systems. Howe...
Generating classification rules from data often leads to large sets of rules that need to be pruned....
AbstractWe present ELEM2, a machine learning system that induces classification rules from a set of ...
Abstract—We present ELEM2, a machine learning system that induces classification rules from a set of...
In the current work, a novel method is presented for generating rules for data classification as wel...
In data mining, rule induction is a process of extracting formal rules from decision tables, where t...
In data mining, rule induction is a process of extracting formal rules from decision tables, where t...
This paper presents a method for data-driven constructive induction, which generates new problemorie...
This paper introduces an algorithm, LEM3, for incremental learning of production rules from examples...
AbstractOur main objective was to compare two discretization techniques, both based on cluster analy...
This paper introduces an algorithm, LEM3, for incremental learning of production rules from examples...
This paper introduces an algorithm, LEM3, for incremental learning of production rules from examples...
Generating classification rules from data often leads to large sets of rules that need to be pruned....
Generating classification rules from data often leads to large sets of rules that need to be pruned....
Generating classification rules from data often leads to large sets of rules that need to be pruned....
Association rule-based classifiers have recently emerged as competitive classification systems. Howe...
Generating classification rules from data often leads to large sets of rules that need to be pruned....
AbstractWe present ELEM2, a machine learning system that induces classification rules from a set of ...
Abstract—We present ELEM2, a machine learning system that induces classification rules from a set of...
In the current work, a novel method is presented for generating rules for data classification as wel...
In data mining, rule induction is a process of extracting formal rules from decision tables, where t...
In data mining, rule induction is a process of extracting formal rules from decision tables, where t...
This paper presents a method for data-driven constructive induction, which generates new problemorie...
This paper introduces an algorithm, LEM3, for incremental learning of production rules from examples...
AbstractOur main objective was to compare two discretization techniques, both based on cluster analy...
This paper introduces an algorithm, LEM3, for incremental learning of production rules from examples...
This paper introduces an algorithm, LEM3, for incremental learning of production rules from examples...
Generating classification rules from data often leads to large sets of rules that need to be pruned....
Generating classification rules from data often leads to large sets of rules that need to be pruned....
Generating classification rules from data often leads to large sets of rules that need to be pruned....
Association rule-based classifiers have recently emerged as competitive classification systems. Howe...
Generating classification rules from data often leads to large sets of rules that need to be pruned....