International audienceIn this paper, a study is presented to explore ensembles of fuzzy decision trees. First of all, a quick recall of the state of the art related to ensembles of (fuzzy) decision trees in Machine Learning is presented. Afterwards, a new approach to construct a forest of fuzzy decision trees is proposed. Two experiments are described, one with forests of fuzzy decision trees, and the other with bagging of fuzzy decision trees. The results highlight the interest of using fuzzy set theory in this kind of approaches
International audienceIn this paper, a video mining method based on the use of Forests of Fuzzy Deci...
One of the general techniques for improving classification accuracy is learning ensembles of classif...
Fuzzy classification is one of the most important applications of fuzzy logic. Its goal is to find a...
Part 3: Data Analysis and Information RetrievalInternational audienceCluster–Context Fuzzy Decision ...
International audienceIn inductive learning, to build decision trees is often arduous when there exi...
The inductive learning methodology known as decision trees, concerns the ability to classify objects...
Abstract:- Decision tree induction is one of common approaches for extracting knowledge from a sets ...
International audienceIn the recent years, forests of decision trees have seen an increasing interes...
This paper proposes a framework which consists of a novel fuzzy inference algorithm to generate fuzz...
Part 7: DecisionsInternational audienceIn this paper a new classification solution which joins C–Fuz...
AbstractWhen individual classifiers are combined appropriately, a statistically significant increase...
There is a lot of approaches for data classification problems resolving. The most significant data c...
Following Breiman’s methodology, we propose a multi-classifier based on a “forest ” of randomly gene...
The last years have seen a remarkable flowering of works about the use of decision trees for ranking...
Classification is a process where a classifier predicts a class label to an object using the set of ...
International audienceIn this paper, a video mining method based on the use of Forests of Fuzzy Deci...
One of the general techniques for improving classification accuracy is learning ensembles of classif...
Fuzzy classification is one of the most important applications of fuzzy logic. Its goal is to find a...
Part 3: Data Analysis and Information RetrievalInternational audienceCluster–Context Fuzzy Decision ...
International audienceIn inductive learning, to build decision trees is often arduous when there exi...
The inductive learning methodology known as decision trees, concerns the ability to classify objects...
Abstract:- Decision tree induction is one of common approaches for extracting knowledge from a sets ...
International audienceIn the recent years, forests of decision trees have seen an increasing interes...
This paper proposes a framework which consists of a novel fuzzy inference algorithm to generate fuzz...
Part 7: DecisionsInternational audienceIn this paper a new classification solution which joins C–Fuz...
AbstractWhen individual classifiers are combined appropriately, a statistically significant increase...
There is a lot of approaches for data classification problems resolving. The most significant data c...
Following Breiman’s methodology, we propose a multi-classifier based on a “forest ” of randomly gene...
The last years have seen a remarkable flowering of works about the use of decision trees for ranking...
Classification is a process where a classifier predicts a class label to an object using the set of ...
International audienceIn this paper, a video mining method based on the use of Forests of Fuzzy Deci...
One of the general techniques for improving classification accuracy is learning ensembles of classif...
Fuzzy classification is one of the most important applications of fuzzy logic. Its goal is to find a...