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1
Enhancing Classification Algorithms with Metaheuristic Technique
Published 2024“…Implementing this process uses classification algorithms such asNaïve Bayes, Support Vector Machine,and Random Forest. …”
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2
Performance comparison of CNN and LSTM algorithms for arrhythmia classification
Published 2020“…However, there is a lack of study that analyzes the performance comparison of CNN and LSTM algorithms for arrhythmia classification. In this paper, the performance of CNN and LSTM algorithms for arrhythmia classification is compared for a publicly available dataset. …”
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3
Utilizing artificial bee colony algorithm as feature selection method in Arabic text classification
Published 2023“…One of the widely used algorithms for feature selection in text classification is the Evolutionary algorithm . …”
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4
Gene subset selection for lung cancer classification using a multi-objective strategy
Published 2008“…However, the urgent problems in the use of gene expression data are the availability of a huge number of genes relative to the small number of available samples, and many of the genes are not relevant to the classification. …”
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5
Comparative analysis of text classification algorithms for automated labelling of quranic verses
Published 2017“…In this paper, we propose to automate the labelling task of the Quranic verse using text classification algorithms. We applied three text classification algorithms namely, k-Nearest Neighbour, Support Vector Machine, and Naïve Bayes in automating the labelling procedure. …”
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6
Support vector classification of remote sensing images using improved spectral Kernels
Published 2008“…Results show that these kernels do in fact improve classification accuracy and use the prior information available in imagery to a better degree.…”
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7
Machine learning-based leukemia classification using gene expression for accurate diagnosis
Published 2025“…The proposed techniques is then compared with the existing approaches using the same dataset. It is observed that the proposed model for leukemia classification has an accuracy of 97% using SVM algorithm whereas 94% is using Logistic regression algorithm.…”
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Proceeding Paper -
8
Functional link neural network with modified bee-firefly learning algorithm for classification task
Published 2016“…MLP usually requires a large amount of available measures in order to achieve good classification accuracy. …”
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9
Performances of machine learning algorithms for binary classification of network anomaly detection system
Published 2018“…Moreover, network anomaly detection using machine learning faced difficulty when dealing the involvement of dataset where the number of labelled network dataset is very few in public and this caused many researchers keep used the most commonly network dataset (KDDCup99) which is not relevant to employ the machine learning (ML) algorithms for a classification. …”
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10
DATA CLASSIFICATION SYSTEM WITH FUZZY NEURAL BASED APPROACH
Published 2005“…The project's objective is identifying the available data mining algorithms in data classification and applying new data mining algorithm to perform classification tasks. …”
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Final Year Project -
11
The Bacterial Foraging Optimisation Algorithm using Prototype Selection and Prototype Generation for Data Classification
Published 2020“…However, none of the available works had proposed BFOA as a classification algorithm despite of its good performance. …”
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12
Improved building roof type classification using correlation-based feature selection and gain ratio algorithms
Published 2017“…The classification results using SVM classifier produced an overall accuracy of 83.16%. …”
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13
Classification of brain tumors: using deep transfer learning
Published 2023“…To achieve the goal, a modified GoogleNet model was used. Various learning algorithms were tested. The experiment also examined transfer learning and data augmentation. …”
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14
SVM for network anomaly detection using ACO feature subset
Published 2016“…But irrelevant and redundant features are the obstacle for classification algorithm to build an efficient detection model. …”
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15
An approach to improve functional link neural network training using modified artificial bee colony for classification task
Published 2013“…However, MLP usually requires a rather large amount of available measures in order to achieve good classification accuracy. …”
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16
An approach to improve functional link neural network training using modified artificial bee colony for classification task
Published 2012“…However, MLP usually requires a rather large amount of available measures in order to achieve good classification accuracy. …”
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17
An approach to improve functional link neural network training using modified artificial bee colony for classification task
Published 2012“…However, MLP usually requires a rather large amount of available measures in order to achieve good classification accuracy. …”
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18
Minimizing Classification Errors in Imbalanced Dataset Using Means of Sampling
Published 2023Conference Paper -
19
Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy
Published 2019“…The proposed algorithm is compared with the state-of-the-art feature selection algorithms using three different datasets. …”
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20
A refined classification approach by integrating Landsat Operational Land Imager (OLI) and RADARSAT-2 imagery for land-use and land-cover mapping in a tropical area
Published 2016“…Determining the best method for mapping with a specific data source and study area is a major challenge because of the wide range of classification algorithms and methodologies available. …”
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