Back to Search
Start Over
Hybrid neural networks for big data classification
- Source :
- Neurocomputing. 390:327-340
- Publication Year :
- 2020
- Publisher :
- Elsevier BV, 2020.
-
Abstract
- Two new hybrid neural architectures combining morphological neurons and perceptrons are introduced in this paper. The first architecture, called Morphological - Linear Neural Network (MLNN) consists of a hidden layer of morphological neurons and an output layer of classical perceptrons has the capability of extracting features. The second architecture, called Linear-Morphological Neural Network (LMNN) is composed of one or several perceptron layers as a feature extractor, it is then followed by an output layer of morphological neurons for non-linear classification. Both architectures are trained by stochastic gradient descent. One of the main contributions of this paper is to show that the morphological layer offers a greater capacity to extract features than the perceptron layer. This claim is supported both theoretically and experimentally. We prove that the morphological layer possesses a greater capacity per computation unit to segment the 2D input space than the perceptron layer. In other words, adding more hyper-boxes produces more response regions than adding hyperplanes. From an empirical point of view, we test the two new models on 25 standard datasets at low dimensionality and one big data dataset. The result is that MLNN requires a lesser number of learning parameters than the other tested architectures while achieving better accuracies.
- Subjects :
- 0209 industrial biotechnology
Artificial neural network
business.industry
Computer science
Cognitive Neuroscience
Pattern recognition
02 engineering and technology
Perceptron
Computer Science Applications
ComputingMethodologies_PATTERNRECOGNITION
020901 industrial engineering & automation
Stochastic gradient descent
Hyperplane
Artificial Intelligence
Multilayer perceptron
0202 electrical engineering, electronic engineering, information engineering
Feature (machine learning)
020201 artificial intelligence & image processing
Artificial intelligence
Layer (object-oriented design)
business
Large margin nearest neighbor
Curse of dimensionality
Subjects
Details
- ISSN :
- 09252312
- Volume :
- 390
- Database :
- OpenAIRE
- Journal :
- Neurocomputing
- Accession number :
- edsair.doi...........31a2872363def64cde98363bbec1f9ea