Search Results - (( probably classification learning algorithm ) OR ( java application using algorithm ))
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A New Probabilistic Output Constrained Optimization Extreme Learning Machine
Published 2023“…Benchmarking; Classification (of information); Constrained optimization; Decision making; Electric power systems; Iterative methods; Knowledge acquisition; Learning algorithms; Pattern recognition; Probability; Confidence threshold; Decision making process; Extreme learning machine; Machine learning approaches; Pattern classification problems; Post-processing procedure; Power system applications; Probabilistic output; Machine learning…”
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Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model
Published 2018“…Hence, this situation is believed in yielding of decreasing the classification accuracy. In this article, we present the exploration on the combination of the clustering based algorithm with an ensemble classification learning. …”
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Lexicon-based and immune system based learning methods in Twitter sentiment analysis
Published 2016“…Nowadays, there are increasingly numbers of studies on seeking ways to mine Twitter for sentiment analysis. Machine learning approach such as immune system based learning methods is an alternative way for sentiment classification.This method is centered on prominent immunological theory as computation mechanisms that emulate processes in biological immune system in achieving higher probability for pattern recognition. …”
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Conference or Workshop Item -
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Predicting breast cancer using ant colony optimisation / Siti Sarah Aqilah Che Ani
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Student Project -
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Classification of chest radiographs using novel anomalous saliency map and deep convolutional neural network
Published 2021“…Therefore, we also introduce the Xenafas algorithm in this paper. The algorithm creates a new kind of anomalous saliency map called the Intensity Probability Mapping and Weighted Intensity Probability Mapping. …”
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Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets
Published 2019“…Classification of imbalanced datasets remained a significant issue in data mining and machine learning (ML) fields. …”
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Thesis -
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Adaptive parameter control strategy for ant-miner classification algorithm
Published 2020“…The ACS algorithm is designed to optimize the IR parameter during the learning process of the Ant-Miner algorithm. …”
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Condition diagnosis of bearing system using multiple classifiers of ANNs and adaptive probabilities in genetic algorithms
Published 2014“…Therefore, finding the best weights in learning process is an important task for obtaining good performance of ANNs.Previous researchers have proposed some methods to get the best weights such as simple average and majority voting.However, these methods have some limitations in providing the best weights especially in condition diagnosis of bearing systems.In this paper, we propose a hybrid technique of multiple classifier-ANNs (mANNs) and adaptive probabilities in genetic algorithms (APGAs) to obtain the best weights of ANNs in order to increase the classification performance of ANNs in condition diagnosis of bearing systems. …”
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Sauvola Segmentation and Support Vector Machine-Salp Swarm Algorithm Approach for Identifying Nutrient Deficiencies in Citrus Reticulata Leaves
Published 2024“…In the next phase, the datasets are optimized using the Salp Swarm Algorithm (SSA), which improves classification accuracy. …”
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Constrained–Optimization-based Bayesian posterior probability extreme learning machine for pattern classification
Published 2023Conference Paper -
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RSA Encryption & Decryption using JAVA
Published 2006“…References and theories to support the research of 'RSA Encryption/Decryption using Java' have been disclosed in Literature Review section. …”
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Final Year Project -
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Provider independent cryptographic tools
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Monograph -
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Affective computation on EEG correlates of emotion from musical and vocal stimuli
Published 2009“…The proposed ABCI extracts EEG features from subjects while exposed to 6 emotionally-related musical and vocal stimuli using kernel smoothing density estimation (KSDE) and Gaussian mixture model probability estimation (GMM). A classification algorithm is subsequently used to learn and classify the extracted EEG features. …”
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Proceeding Paper -
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Class binarization with self-adaptive algorithm to improve human activity recognition
Published 2018“…However, the learning complexity of classification is increased due to the expansion number of learning model. …”
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