Probabilistic Decision Trees using SVM for Multi-class Classification

When used for speaker recognition, decision trees are usually trained to learn a decision boundary between speaker and non- speaker speech patterns, using for instance the

Development of an intelligent agent-based model of the epidemic process of syphilis, International Scientific and Technical Conference on Computer Sciences and

The Classification of Insincere Questions task at FIRE 2019 did not just fo- cus on binary classification of insincere questions, but went a step further and introduced a

The aim of the paper is to evaluate the ability of di↵erent decision tree classifiers for cultural heritage image classification involving a small sample, based on three types

Dynamic programming (DP) on tree decompositions is a well studied approach for solving hard problems efficiently.. State-of-the-art implementations usually rely on tables for stor-

Computer interfaces provide an environment that allows for multiple objectively optimal solutions but individuals will, over time, use a smaller number of subjectively

In order to evaluate the effec- tiveness of the proposed multi-task learning frame- work, we compare our one-class SVM based multi- task learning method (denoted by MTL-OSVM) with

We also show that the use of belief functions allows us to combine the information contained into different input data derived from the whole spectrum data, and that it is an