Part 3: Data Analysis and Information RetrievalInternational audienceCluster–Context Fuzzy Decision Tree is the classifier which joins C–Fuzzy Decision Tree with Context–Based Fuzzy Clustering method. The idea of using this kind of tree in the Fuzzy Random Forest is presented in this paper. The created ensemble classifier has similar assumptions to the Fuzzy Random Forest, but differs in the kind of used trees and all aspects connected with this difference. The quality of the created classifier was evaluated by several experiments performed on different datasets. There were tested both datasets with discrete and continuous attributes and decision classes. The aspect of using a randomness in the created classifier was also evaluated
Random forests are currently considered among the most accurate and efficient classifiers. Moreover,...
Abstract:- Decision tree induction is one of common approaches for extracting knowledge from a sets ...
Random forest is a popular machine learning algorithm which is made up of an ensemble of decision tr...
Part 7: DecisionsInternational audienceIn this paper a new classification solution which joins C–Fuz...
International audienceIn this paper, a study is presented to explore ensembles of fuzzy decision tre...
AbstractWhen individual classifiers are combined appropriately, a statistically significant increase...
Following Breiman’s methodology, we propose a multi-classifier based on a “forest ” of randomly gene...
Random forests have proved to be very effective classifiers, which can achieve very high accuracies....
International audienceIn the recent years, forests of decision trees have seen an increasing interes...
International audienceIn this paper we present a study on the random forest (RF) family of ensemble ...
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...
Classification is a process where a classifier predicts a class label to an object using the set of ...
Abstract — Regardless of creation method, Fuzzy rules are of great importance in the implementation ...
International audienceForest of fuzzy decision trees are known to be a powerful machine learning too...
Random forests are currently considered among the most accurate and efficient classifiers. Moreover,...
Abstract:- Decision tree induction is one of common approaches for extracting knowledge from a sets ...
Random forest is a popular machine learning algorithm which is made up of an ensemble of decision tr...
Part 7: DecisionsInternational audienceIn this paper a new classification solution which joins C–Fuz...
International audienceIn this paper, a study is presented to explore ensembles of fuzzy decision tre...
AbstractWhen individual classifiers are combined appropriately, a statistically significant increase...
Following Breiman’s methodology, we propose a multi-classifier based on a “forest ” of randomly gene...
Random forests have proved to be very effective classifiers, which can achieve very high accuracies....
International audienceIn the recent years, forests of decision trees have seen an increasing interes...
International audienceIn this paper we present a study on the random forest (RF) family of ensemble ...
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...
Classification is a process where a classifier predicts a class label to an object using the set of ...
Abstract — Regardless of creation method, Fuzzy rules are of great importance in the implementation ...
International audienceForest of fuzzy decision trees are known to be a powerful machine learning too...
Random forests are currently considered among the most accurate and efficient classifiers. Moreover,...
Abstract:- Decision tree induction is one of common approaches for extracting knowledge from a sets ...
Random forest is a popular machine learning algorithm which is made up of an ensemble of decision tr...