Search Results - (( data optimization method algorithm ) OR ( data classification method algorithm ))
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1
Application of Optimization Methods for Solving Clustering and Classification Problems
Published 2011“…The data vectors are assigned to the closest cluster and correspondingly to the set, which contains this cluster and an algorithm based on a derivative-free method is applied to the solution of this problem. …”
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2
Attribute related methods for improvement of ID3 Algorithm in classification of data: A review
Published 2020“…Decision tree is an important method in data mining to solve the classification problems. …”
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3
Fuzzy modeling using Bat Algorithm optimization for classification
Published 2018“…In order to solve it, Bat Algorithm method is implement in to optimization method in fuzzy modeling for classification. …”
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Undergraduates Project Papers -
4
A derivative-free optimization method for solving classification problem
Published 2010“…One of the most promising ways to data classification is based on methods of mathematical optimization. …”
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5
Logistic regression methods for classification of imbalanced data sets
Published 2012“…Thus, both proposed imbalanced LR-based methods is simple and effective for classification of imbalanced data sets and have promising results.…”
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Enhancing Classification Algorithms with Metaheuristic Technique
Published 2024“…However, the classification algorithm cannotclassify data optimally due to the challenges in dealing with variousdata sets. …”
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Optimized feature construction methods for data summarizations of relational data
Published 2014“…The summarized data will then be fed to any classification algorithm to perform the classification task. …”
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Application of the bees algorithm to the selection features for manufacturing data
Published 2007“…The Bees Algorithm is employed to select an optimal set of features for a particular pattern classification task. …”
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Conference or Workshop Item -
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Ideal combination feature selection model for classification problem based on bio-inspired approach
Published 2020“…Such a finding indicates that the exploitation of bio-inspired algorithms with ideal combination of wrapper/filtered method can contribute in finding the optimal features to be used in data mining model construction.…”
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Book Section -
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A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem
Published 2016“…There are two methods in dealing with imbalanced classification problem, which are based on data or algorithmic level. …”
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11
Feature and Instances Selection for Nearest Neighbor Classification via Cooperative PSO
Published 2014“…The reduction method contains two techniques, namely features reduction and data reduction which are commonly applied to a classification problem. …”
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Conference or Workshop Item -
12
Taylor-Bird Swarm Optimization-Based Deep Belief Network For Medical Data Classification
Published 2022“…Various medical data classification methods are developed in the existing research works, but achieving higher classification accuracy is a great challenge in the medical sector due to the presence of noisy, and high-dimensional data. …”
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13
An ensemble learning method for spam email detection system based on metaheuristic algorithms
Published 2015“…In the second phase, a classifier ensemble learning model is proposed consisting of separate outputs: (i) To select a relevant subset of original features based on Binary Quantum Gravitational Search Algorithm (QBGSA), (ii) To mine data streams using various data chunks and overcome a failure of single classifiers based on SVM, MLP and K-NN algorithms. …”
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14
Gender classification on skeletal remains: efficiency of metaheuristic algorithm method and optimized back propagation neural network
Published 2020“…Based on the feature selection results, the Optimized BPNN outperformed other methods for all datasets. …”
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Article -
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Optimized tree-classification algorithm for classification of protein sequences
Published 2016“…The problem of classifying protein sequences based on the primary sequence information is a very complex and challenging task in the analysis and understanding of sequenced data. The existing classification methods are performing well on a very limited data; however the rapid increase in the genomic data leads to the development of improved computational methods. …”
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Conference or Workshop Item -
16
Optimized tree-classification algorithm for classification of protein sequences
Published 2016“…The problem of classifying protein sequences based on the primary sequence information is a very complex and challenging task in the analysis and understanding of sequenced data. The existing classification methods are performing well on a very limited data; however the rapid increase in the genomic data leads to the development of improved computational methods. …”
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17
A modified weighted support vector machine (WSVM) to reduce noise data in classification problem
Published 2021“…To overcome SVM drawback for noise data problem, WSVM using KPCM algorithm was used but WSVM using kernel-based learning algorithm such as KPCM algorithm suffer from training complexity, expensive computation time and storage memory when noise data contaminate training data. …”
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18
A modified weighted support vector machine (WSVM) to reduce noise data in classification problem
Published 2021“…To overcome SVM drawback for noise data problem, WSVM using KPCM algorithm was used but WSVM using kernel-based learning algorithm such as KPCM algorithm suffer from training complexity, expensive computation time and storage memory when noise data contaminate training data. …”
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An improved particle swarm optimization algorithm for data classification
Published 2023“…Optimisation-based methods are enormously used in the field of data classification. …”
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Article -
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Training functional link neural network with ant lion optimizer
Published 2020“…From the result achieved, it can be seen that the implementation of the proposed learning algorithm for FLNN performs the classification task quite well and yields better accuracy on the unseen data…”
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