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1
An ensemble learning method for spam email detection system based on metaheuristic algorithms
Published 2015“…Feature subset selection and classifier ensemble learning are familiar techniques with high ability to optimize above problems. Recently, various techniques based on different algorithms have been developed. …”
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2
Classification System for Heart Disease Using Bayesian Classifier
Published 2007“…Increase of hearth problem in this world is rising each day. Classification system for heart disease is a system that able to justify whether a patient has heart problem or not. …”
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3
Fuzzy modeling using Bat Algorithm optimization for classification
Published 2018“…A Sazonov Engine which is a fuzzy java engine is use to apply Bat Algorithm in the experiment. …”
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Undergraduates Project Papers -
4
A novel hybrid classification model of genetic algorithms, modified k-Nearest Neighbor and developed backpropagation neural network
Published 2014“…Among numerous artificial intelligence approaches, k-Nearest Neighbor algorithms, genetic algorithms, and artificial neural networks are considered as the most common and effective methods in classification problems in numerous studies. …”
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Article -
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Modified word representation vector based scalar weight for contextual text classification
Published 2024“…For this experiment, the modified word vectors serve as input to train a Machine Learning (ML) model for the text classification process, aiming for the developed ML model to have a significantly smaller parameter count. …”
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6
The Bacterial Foraging Optimisation Algorithm using Prototype Selection and Prototype Generation for Data Classification
Published 2020“…There are two modified instance-based classifiers of BFOA were developed in this study. …”
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Application Of Neural Network In Malaria Parasites Classification
Published 2006“…Hybrid Multilayer Perceptron (HMLP) network with modified recursive prediction error algorithm will be developed using Borland C++ Builder. …”
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Monograph -
8
Modified archive update mechanism of multi-objective particle swarm optimization in fuzzy classification and clustering
Published 2022“…According to the literature, crowding distance as one of the most efficient algorithms was developed based on density measures to treat the problem of selection mechanism for archive update. …”
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9
Development of Phasor Measurement Unit Based Fault Detection and Faulty Line Classification in Electrical Power System
Published 2019“…Thirdly, for a faulty line classification (FLC), this study develops the current angles differential scheme by introducing unwrapped dynamic phase angles using the modified PMU measurements. …”
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10
Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde
Published 2022“…This thesis is based on the application of sentiment classification algorithm to tweet data with the goal of classifying messages based on the polarity of sentiment towards a particular topic (or subject matter). …”
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11
Web-based expert system for material selection of natural fiber- reinforced polymer composites
Published 2015“…So, the integration of Artificial Neural Network (ANN) with an Expert System for material classification was explored. The computational tool, Matlab was proposed for classification with Levenberg-Marquardt training algorithm, which provided faster rate of convergence for feed forward network. …”
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12
Aco-based feature selection algorithm for classification
Published 2022“…The modified graph clustering ant colony optimisation (MGCACO) algorithm is an effective FS method that was developed based on grouping the highly correlated features. …”
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13
Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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14
Enhanced grey wolf optimisation algorithm for feature selection in anomaly detection
Published 2022“…Experimental results of the EBGWO algorithm on the NSL-KDD dataset in terms of number of selected features and classification accuracy are superior to other benchmark optimisation algorithms. …”
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Logistic regression methods for classification of imbalanced data sets
Published 2012“…This thesis aims to develop the simple and effective imbalanced classification algorithms by previously improving the algorithms performance of general classifiers i.e. …”
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17
A Hybrid Rough Sets K-Means Vector Quantization Model For Neural Networks Based Arabic Speech Recognition
Published 2002“…In this thesis rough sets approach was used in the preprocessing stages, namely in the vector quantization operation in which feature vectors are quantized or classified to a finite set of codebook classes. Classification rules were generated from training feature vectors set, and a modified form of the standard voter classification algorithm, that use the rough sets generated rules, was applied. …”
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18
Feature fusion using a modified genetic algorithm for face and signature recognition system
Published 2015“…To overcome the issue of incompatible features to be combined, Wrapper Genetic Algorithm (GA) was implemented as the feature selection algorithm due to its ability to evaluate the features irrespective of which domain by masking the features with bit number. …”
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19
Object-Oriented Programming semantics representation utilizing agents
Published 2011“…Generally, these source codes go through the preprocessing, comparison, extraction, generate program semantics and classification processes. A formal algorithm that can be applied to any two related Java-based source codes examples is invented to generate the semantics of these source codes. …”
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Article -
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Comparative analysis of convolutional neural network frameworks for efficient classification of calcification patches in Digital Breast Tomosynthesis images / Nurhazwani Mohamad Fo...
Published 2025“…A comparative analysis of CNN models including GoogleNet, SqueezeNet, modified GoogleNet and modified SqueezeNet is conducted to determine their classification performance. …”
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