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1
Functional link neural network with modified bee-firefly learning algorithm for classification task
Published 2016“…The aim is to introduce an improved learning algorithm that can provide a better solution for training the FLNN network for the task of classification…”
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Thesis -
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
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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4
Classification of brain tumors: using deep transfer learning
Published 2023“…Experimenters employed data augmentation and learning algorithms.…”
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5
Machine learning-based leukemia classification using gene expression for accurate diagnosis
Published 2025“…Given the availability of gene expression data, machine learning algorithms have demonstrated considerable promise in recent years for enhancing the accuracy of leukemia classification. …”
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Proceeding Paper -
6
Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy
Published 2019“…In the second part of the study, a novel classification algorithm called Hessian semi-supervised ELM (HSS-ELM) is proposed to enhance the semi-supervised learning of ELM. …”
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7
Minimizing Classification Errors in Imbalanced Dataset Using Means of Sampling
Published 2023Conference Paper -
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An approach to improve functional link neural network training using modified artificial bee colony for classification task
Published 2013“…The standard method for tuning the weight in FLNN is using a Backpropagation (BP) learning algorithm. Still, BP-learning algorithm has difficulties such as trapping in local optima and slow convergence especially for solving non-linearly separable classification problems. …”
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9
An approach to improve functional link neural network training using modified artificial bee colony for classification task
Published 2012“…The standard method for tuning the weight in FLNN is using a Backpropagation (BP) learning algorithm. Still, BP-learning algorithm has difficulties such as trapping in local optima and slow convergence especially for solving non-linearly separable classification problems. …”
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10
An approach to improve functional link neural network training using modified artificial bee colony for classification task
Published 2012“…The standard method for tuning the weight in FLNN is using a Backpropagation (BP) learning algorithm. Still, BP-learning algorithm has difficulties such as trapping in local optima and slow convergence especially for solving non-linearly separable classification problems. …”
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11
Diabetes Diagnosis And Level Of Care Fuzzy Rule-Based Model Utilizing Supervised Machine Learning For Classification And Prediction
Published 2024“…Most computer applications use machine learning and data mining techniques to aid classification and prediction of a disease. …”
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12
Machine learning: tasks, modern day applications and challenges
Published 2019“…During the last decade, we have witnessed significant development in artificial intelligence (AI) capabilities and its application areas such as healthcare, self-driving cars, eLearning, military, smart cities, industry, etc. Machine learning algorithms learned from available data. …”
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13
Enhancing Classification Algorithms with Metaheuristic Technique
Published 2024“…So,the selection of features is minimaland is not based on the previous learning process or what is known as heuristics. For this reason, in this research,several auxiliary algorithms are introduced to improve the performance of the classification algorithm, namely the meta-heuristic algorithm. …”
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14
Support vector classification of remote sensing images using improved spectral Kernels
Published 2008“…In the case of hyper-spectral imagery the amount of information available prior to classification is a vast amount. …”
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15
RSA Encryption & Decryption using JAVA
Published 2006“…The implementation of this project will be based on Rapid Application Design Methodology (RAD) and will be more focusing on research and finding, ideas and the implementation of the algorithm, and finally running and testing the algorithm. …”
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Final Year Project -
16
Building extraction of worldview3 imagery via support vector machine using scikit-learn module / Najihah Ismail
Published 2021“…Consequently, this study is intending to apply Support Vector Machine (SVM) classification which using Scikit-learn module for building classification. …”
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17
An improvement of back propagation algorithm using halley third order optimisation method for classification problems
Published 2020“…Back Propagation (BP) has proven to be a robust algorithm for different connectionist learning problems which commonly available for any functional induction that provides a computationally efficient method. …”
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18
Ensemble-based machine learning algorithms for classifying breast tissue based on electrical impedance spectroscopy
Published 2020“…The application of artificial intelligence techniques (e.g., machine learning and deep learning) in medical science is becoming increasingly important for intelligently transforming all available information into valuable knowledge. …”
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Genetic algorithm fuzzy logic for medical knowledge-based pattern classification
Published 2018“…This research proposed an algorithm named Genetic Algorithm Fuzzy Logic (GAFL) with Pittsburg approach for rules learning and induction in genetic fuzzy system knowledge discovery. …”
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