Randomness in Circular - Complex Extreme Learning Machine Vs Voting Based Extreme Learning Machine with Accuracy Based Ensemble Pruning: A Review
نویسندگان
چکیده
منابع مشابه
Voting based Extreme Learning Machine with Accuracy based ensemble Pruning
Extreme Learning Machine is a fast single layer feed forward neural network for real valued classification. It suffers from the problem of instability and over fitting. Voting based Extreme Learning Machine, VELM reduces this performance variation in Extreme Learning Machine by employing majority voting based ensembling technique. VELM improves the performance of ELM at the cost of increased re...
متن کاملExtreme Learning Machine: A Review
Feedforward neural networks (FFNN) have been utilised for various research in machine learning and they have gained a significantly wide acceptance. However, it was recently noted that the feedforward neural network has been functioning slower than needed. As a result, it has created critical bottlenecks among its applications. Extreme Learning Machines (ELM) were suggested as alternative learn...
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This paper proposes a novel method for supervised subspace learning based on Single-hidden Layer Feedforward Neural networks. The proposed method calculates appropriate network target vectors by formulating a Bayesian model exploiting both the labeling information available for the training data and geometric properties of the training data, when represented in the feature space determined by t...
متن کاملDynamic ensemble extreme learning machine based on sample entropy
Extreme learning machine (ELM) as a new learning algorithm has been proposed for single-hidden layer feed-forward neural networks, ELM can overcome many drawbacks in the traditional gradient-based learning algorithm such as local minimal, improper learning rate, and low learning speed by randomly selecting input weights and hidden layer bias. However, ELM suffers from instability and over-fitti...
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Recently, a new learning algorithm for the feedforward neural network named the extreme learning machine (ELM) which can give better performance than traditional tuning-based learning methods for feedforward neural networks in terms of generalization and learning speed has been proposed by Huang et al. In this paper, we first extend the ELM algorithm from the real domain to the complex domain, ...
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ژورنال
عنوان ژورنال: IARJSET
سال: 2019
ISSN: 2394-1588,2393-8021
DOI: 10.17148/iarjset.2019.6510