Search Results - (( parameter classification learning algorithm ) OR ( quality classification using algorithm ))
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Comparison of Logistic Regression, Random Forest, SVM, KNN Algorithm for Water Quality Classification Based on Contaminant Parameters
Published 2024“…This study compares four machine learning algorithms Logistic Regression, Random Forest, Support Vector Machine (SVM), and K-Nearest Neighbors (KNN) in water quality classification based on contaminant parameters. …”
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Classification of diabetic retinopathy clinical features using image enhancement technique and convolutional neural network / Abdul Hafiz Abu Samah
Published 2021“…To solving pattern classification problem, the optimization deep learning architecture and parameter by using four convolution layers is set up to classify the three pathological signs; HEM, MA and exudate. …”
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Software defect prediction framework based on hybrid metaheuristic optimization methods
Published 2015“…The classification algorithm is a popular machine learning approach for software defect prediction. …”
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Water Quality Evaluation and Analysis by Integrating Statistical and Machine Learning Approaches
Published 2026journal::journal article -
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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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Extremal region detection and selection with fuzzy encoding for food recognition
Published 2019“…The first algorithm locates interest points in food images using an MSER. …”
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Oil palm maturity classifier using spectrometer and machine learning
Published 2021“…The prediction was able to produce 100% accuracies by using Linear and Weighted KNN as classification testing algorithm. …”
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Backpropagation algorithm for classification problem: academic performance prediction model for UiTM Melaka Mengubah Destini Anak Bangsa (MDAB) program. / Fadhlina Izzah Saman, Nur...
Published 2012“…Multilayer perceptrons (MLPs) is one of the topology used for processing ANN, while backpropagation algorithm is one of the most popular methods in training MLPs. …”
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Artificial intelligence system for pineapple variety classification and its quality evaluation during storage using infrared thermal imaging
Published 2022“…Several machine learning algorithms including linear discriminant analysis, quadratic discriminant analysis, k-nearest neighbour, support vector machine, decision tree, and Naïve Bayes were applied for the classification of pineapple varieties. …”
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Personalized Recommendation Classification Model of Students’ Social Well-being Based on Personality Trait Determinants Using Machine Learning Algorithms
Published 2023“…In this study, how different personality trait models compare in terms of accuracy and reliability is explored using different machine learning algorithms using the WEKA tool. …”
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Improved personalised data modelling using parameter independent fuzzy weighted k-nearest neighbour for spatio/spectro-temporal data
Published 2021“…Upon exploration of the architecture, the weighted k-nearest neighbours algorithm used for the classification module is found to be prone to misclassification as it relies solely on the majority voting rule to determine the class for new data vector. …”
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A stacked ensemble deep learning model for water quality prediction / Wong Wen Yee
Published 2023“…Therefore, this paper aims to explore the use of ensemble and deep learning techniques to simplify the classification process of imbalanced data. …”
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A joint Bayesian optimization for the classification of fine spatial resolution remotely sensed imagery using object-based convolutional neural networks
Published 2022“…This paper presents a novel approach for combining convolutional neural networks (CNN) with OBIA based on joint optimization of segmentation parameters and deep feature extraction. A Bayesian technique was used to find the best parameters for the multiresolution segmentation (MRS) algorithm while the CNN model learns the image features at different layers, achieving joint optimization. …”
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An enhanced gated recurrent unit with auto-encoder for solving text classification problems
Published 2020“…Gated Recurrent Unit (GRU) is a type of Recurrent Neural Networks (RNNs), and a deep learning algorithm that contains update gate and reset gate. …”
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A framework of modified adaptive neuro-fuzzy inference engine
Published 2012“…The developed TSK type fuzzy inference engine is called modified adaptive fuzzy inference engine (MAFIE) and its parameters were then adjusted by the hybrid learning algorithm using adaptive neural network architecture towards improved performance which is called MANFIE. …”
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Predicting noise-induced hearing loss (NIHL) in TNB workers using GDAM algorithm
Published 2012“…This research proposed an algorithm for improving the current working performance of Back-propagation algorithm by adaptively changing the momentum value and at the same time keeping the ‘gain’ parameter fixed for all nodes in the neural network. …”
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Application of artificial neural network in discriminating the agarwood oil quality using significant chemical compounds / Mohd Hezri Fazalul Rahiman … [et al.]
Published 2014“…Back-propagation training algorithm and sigmoid transfer function were used to optimise the parameters in the training network. …”
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Improving multi-resident activity recognition in smart home using multi label classification with adaptive profiling
Published 2018“…Furthermore, there is tendency that multi label classifications used instead of traditional single label classification technique. …”
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Monitoring water quality in Pusu river using Internet of Things (IoT) and Machine Learning (ML)
Published 2024“…Machine learning (ML) tools will be employed to analyze and simulate these data, enabling the prediction of future water quality parameters. …”
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