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What is Multilayer Perceptron

Chapter 8
Handbook of Research on Applications and Implementations of Machine Learning Techniques
Multilayer perceptron falls under artificial neural networks (ANN). It is a feed forward network that consists of a minimum of three layers of nodes- an input layer, one or more hidden layers and an output layer. It uses a supervised learning technique, namely, back propagation for training. Its main advantage is that it has the ability to distinguish data that is not linearly separable.
Published in Chapter:
Machine Learning in Python: Diabetes Prediction Using Machine Learning
Astha Baranwal (VIT University, India), Bhagyashree R. Bagwe (VIT University, India), and Vanitha M (VIT University, India)
Copyright: © 2020 |Pages: 27
DOI: 10.4018/978-1-5225-9902-9.ch008
Abstract
Diabetes is a disease of the modern world. The modern lifestyle has led to unhealthy eating habits causing type 2 diabetes. Machine learning has gained a lot of popularity in the recent days. It has applications in various fields and has proven to be increasingly effective in the medical field. The purpose of this chapter is to predict the diabetes outcome of a person based on other factors or attributes. Various machine learning algorithms like logistic regression (LR), tuned and not tuned random forest (RF), and multilayer perceptron (MLP) have been used as classifiers for diabetes prediction. This chapter also presents a comparative study of these algorithms based on various performance metrics like accuracy, sensitivity, specificity, and F1 score.
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Chapter 139
Malware Detection in Network Flows With Self-Supervised Deep Learning
Also known as an MLP neural network, they are a type of deep learning neural network algorithm that is composed of multiple layers of perceptrons. They contain at least one “hidden” layer of perceptrons within their network, and all MLP models contain an input layer, at least one hidden layer and an output layer. The MLP models generally contain a non-linear activation function and thus have sensitivities to non-linear relationships present in the dataset. MLP models are typically referred to as “vanilla” neural networks, as opposed to recurrent neural networks, convolutional neural networks and other more mission-specific forms of neural networks.
Published in Chapter: Malware Detection in Network Flows With Self-Supervised Deep Learning; From: Encyclopedia of Data Science and Machine Learning
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Chapter 21
Application of Neural Networks in Animal Science
The most well know and most widely used neural mdel in problems such as: systems modelization, time-series prediction and, pattern classification. The name stands for the location of the neurons in several layers.
Published in Chapter: Application of Neural Networks in Animal Science; From: Handbook of Research on Machine Learning Applications and Trends: Algorithms, Methods, and Techniques
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Chapter 16
Arrhythmia Detection and Classification Using Wavelet and ICA
A class of networks consists of multiple layers of computational units, usually interconnected in a feed-forward way.
Published in Chapter: Arrhythmia Detection and Classification Using Wavelet and ICA; From: Encyclopedia of Healthcare Information Systems
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Chapter 20
Application to Bankruptcy Prediction in Banks
A specific kind of artificial neural network whose neurons are organized in sequential layers and where the connections amongst neurons are established only amongst the neurons of two subsequent layers.
Published in Chapter: Application to Bankruptcy Prediction in Banks; From: Handbook of Research on Machine Learning Applications and Trends: Algorithms, Methods, and Techniques
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Chapter 625
Artificial Neural Networks in Physical Therapy
an important class of ANN that typically consists of the input layer, one or more hidden layers of computation nodes, and an output layer. The input signal propagates through the network in a forward direction, on a layer-by-layer basis.
Published in Chapter: Artificial Neural Networks in Physical Therapy; From: Encyclopedia of Information Science and Technology, Third Edition
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Chapter 13
Voice and Speech Recognition Application in Emotion Detection: A Utility for Future Trends
A multilayer perceptron (MLP) is a feedforward artificial neural network that generates a set of outputs from a set of inputs. An MLP is characterized by several layers of input nodes connected as a directed graph between the input and output layers.
Published in Chapter: Voice and Speech Recognition Application in Emotion Detection: A Utility for Future Trends; From: Federated Learning and AI for Healthcare 5.0
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