Experiments on Solving Multiclass Learning Problems by n2-classifier
نویسندگان
چکیده
The paper presents an experimental study of solving multiclass learning problems by a method called n-classifier. This approach is based on training (n − n)/2 binary classifiers one for each pair of classes. Final decision is obtained by a weighted majority voting rule. The aim of the computational experiment is to examine the influence of the choice of a learning algorithm on a classification performance of the n-classifier. Three different algorithms are considered: decision trees, neural networks and instance based learning algorithm.
منابع مشابه
Effectiveness of Error Correcting Output Codes in Multiclass Learning Problems
Classification (machine learning): How does one algorithmically classify the though a more effective approach could be using error correcting codes: @(cs/9501101) Solving Multiclass Learning Problems via Error-Correcting Output Codes. to solving machine learning problems can be broadly useful.
متن کاملCombining Multiple Pairwise Neural Networks Classifiers: A Comparative Study
Classifier combination constitutes an interesting approach when solving multiclass classification problems. We review standard methods used to decode the decomposition generated by a one-against-one approach. New decoding methods are proposed and are compared to standard methods. A stacking decoding is also proposed and consists in replacing the whole decoding by a trainable classifier to arbit...
متن کاملThe Multiclass ROC Front method for cost-sensitive classification
This paper addresses the problem of learning a multiclass classification system that can suit to any environment. By that we mean that particular (imbalanced) misclassification costs are taken into account by the classifier for predictions. However, these costs are not well known during the learning phase in most cases, or may evolve afterwards. There is a need in that case to learn a classifie...
متن کاملOn the Algorithmic Implementation of Multiclass Kernel-based Vector Machines
In this paper we describe the algorithmic implementation of multiclass kernel-based vector machines. Our starting point is a generalized notion of the margin to multiclass problems. Using this notion we cast multiclass categorization problems as a constrained optimization problem with a quadratic objective function. Unlike most of previous approaches which typically decompose a multiclass probl...
متن کاملEnsemble Approaches of Support Vector Machines for Multiclass Classification
Support vector machine (SVM) which was originally designed for binary classification has achieved superior performance in various classification problems. In order to extend it to multiclass classification, one popular approach is to consider the problem as a collection of binary classification problems. Majority voting or winner-takes-all is then applied to combine those outputs, but it often ...
متن کامل