A tool to obtain a classifier system from labelled databases is presented. The result is a hierarchical set of rules to divide the space in n-orthohedrons. This hierarchy means that obtained rules must be applied in specific order, that is, an example will be classify by i-rule only if it isn't matched the conditions of the i-1 preceding rules. It is used a genetic algorithm with real codification as searching method. Logically, computation time will be greater than other systems like C4.5, but it will provide flexibility to the user because it is always possible to produce rules set with 0% of error rate and, from here, to relax the error rate for having less rules. Afterwards, a qualitative approach is made to obtain a linguistic ...
Classifier systems are highly parallel, rule-based learning systems which are designed to continuous...
AbstractRecently, use of a Learning Classifier System (LCS) has become promising method for performi...
AbstractIn many real application areas, the data used are highly skewed and the number of instances ...
This paper describes a new approach, HIDER (HIerarchical DEcision Rules), for learning rules in con...
This paper describes a new approach, HIerarchical DEcision Rules (HIDER), for learning generalizabl...
This paper describes an approach based on evolutionary algorithms, hierarchical decision rules (HID...
This research presents a system for post processing of data that takes mined flat rules as input and...
Abstract. Rule systems have failed to attract much interest in large data analysis problems because ...
Automated discovery of Rule is, due to its applicability, one of the most fundamental and important ...
This article describes a new system for learning rules using rotated hyperboxes as individuals of a ...
The paper presents a method of rule extraction from the trained neural network by means of a genetic...
Abstract—This paper describes an approach based on evo-lutionary algorithms, hierarchical decision r...
In many real application areas, the data used are highly skewed and the number of instances for som...
This paper shows how linguistic classification knowledge can be extracted from numerical data for pa...
The process of automatically extracting novel, useful and ultimately comprehensible information from...
Classifier systems are highly parallel, rule-based learning systems which are designed to continuous...
AbstractRecently, use of a Learning Classifier System (LCS) has become promising method for performi...
AbstractIn many real application areas, the data used are highly skewed and the number of instances ...
This paper describes a new approach, HIDER (HIerarchical DEcision Rules), for learning rules in con...
This paper describes a new approach, HIerarchical DEcision Rules (HIDER), for learning generalizabl...
This paper describes an approach based on evolutionary algorithms, hierarchical decision rules (HID...
This research presents a system for post processing of data that takes mined flat rules as input and...
Abstract. Rule systems have failed to attract much interest in large data analysis problems because ...
Automated discovery of Rule is, due to its applicability, one of the most fundamental and important ...
This article describes a new system for learning rules using rotated hyperboxes as individuals of a ...
The paper presents a method of rule extraction from the trained neural network by means of a genetic...
Abstract—This paper describes an approach based on evo-lutionary algorithms, hierarchical decision r...
In many real application areas, the data used are highly skewed and the number of instances for som...
This paper shows how linguistic classification knowledge can be extracted from numerical data for pa...
The process of automatically extracting novel, useful and ultimately comprehensible information from...
Classifier systems are highly parallel, rule-based learning systems which are designed to continuous...
AbstractRecently, use of a Learning Classifier System (LCS) has become promising method for performi...
AbstractIn many real application areas, the data used are highly skewed and the number of instances ...