Combining multi-layer perceptrons in classification problems
نویسندگان
چکیده
منابع مشابه
Classification using multi-layered perceptrons
There has been an increasing interest in the applicability of neural networks in disparate domains. In this paper, we describe the use of multi-layered perceptrons, a type of neural network topology, for financial classification problems, with promising results. Backpropagation, which is the learning algorithm most often used in multilayered perceptrons, however, is inherently an inefficient se...
متن کاملCombining Missing Data Imputation and Pattern Classification in a Multi-Layer Perceptron
Multi-Layer Perceptrons (MLPs) have been successfully applied in many pattern classification tasks. However, a drawback of these learning machines is that they cannot handle input vectors that present missing data on its features. A recommended way for dealing with missing values is imputation, i.e., to fill in missing data with plausible values. This paper presents a brief review of handling m...
متن کاملPerformance Comparisons Between Backpropagation Networks and Classification Trees on Three Real-World Applications
Etienne Barnard Carnegie-Mellon University Multi-layer perceptrons and trained classification trees are two very different techniques which have recently become popular. Given enough data and time, both methods are capable of performing arbitrary non-linear classification. We first consider the important differences between multi-layer perceptrons and classification trees and conclude that ther...
متن کاملSupport vector machines vs multi-layer perceptrons in particle identification
In this paper we e v aluate the performance of Support Vector Machines SVMs and Multi-Layer Perceptrons MLPs on two diierent problems of Particle Identiication in High Energy Physics experiments. The obtained results indicate that SVMs and MLPs tend to perform very similarly.
متن کاملThe Design and Complexity of Exact Multilayered Perceptrons
We investigate the network complexity of multi-layered perceptrons for solving exactly a given problem. We limit our study to the class of combinatorial optimization problems. It is shown how these problems can be reformulated as binary classification problems and how they can be solved by multi-layered perceptrons.
متن کامل