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Cross-project software defect prediction
Published 2022“…In this work, five research questions covering the classification algorithms, dataset, independent variables, performance evaluation metrics used in CPDP studies, and as well as the performance of individual machine learning classification algorithms in predicting software defects across different software projects were addressed accordingly. …”
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Enhancing understanding of programming concepts through physical games
Published 2017“…We produced in total 10 lesson games to illustrate variables, swapping, arrays, sorting algorithm particularly bubble sort, quicksort, selection sort, graph theory, dynamic programming, amortized analysis and trees. …”
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Tangible interaction learning model to enhance learning activity processes among children with dyslexia
Published 2024“…To find optimum variables, Machine Learning approach needs to be utilized. …”
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Fuzzy subtractive clustering (FSC) with exponential membership function for heart failure disease clustering
Published 2022“…It simulated and processed using Fuzzy Subtractive Clustering Algorithm, Jupyter Notebook Software with Python programming language. …”
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Intelligent imputation method for mix data-type missing values to improve data quality
Published 2024“…To find optimum variables, Machine Learning approach needs to be utilized. …”
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Improving Classification Accuracy of Scikit-learn Classifiers with Discrete Fuzzy Interval Values
Published 2020“…Understanding machine learning (ML) algorithm from scratch is time consuming. …”
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Machine learning techniques for reference evapotranspiration and rice irrigation requirements prediction: a case study of Kerian irrigation scheme, Malaysia
Published 2025“…The novelty of this paper is the application of machine learning techniques as an alternative to traditional methods and software solutions for estimating ETo and irrigation demand. …”
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Input significance analysis: Feature selection through synaptic weights manipulation for EFuNNs classifier
Published 2017“…Specifically for the classification process, Big Data can cause the classifiers to process longer than necessary, and the redundant or irrelevant data may misguide the learning classification algorithms to learn the random error or noise related to them. …”
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Model Prediction Of Pm2.5 And Pm10 Using Machine Learning Approach
Published 2021“…It was found that taking into account the removal of the irrelevant variables does not increase precision significantly nor does it reduce the performance tremendously. …”
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Recommendation System Model For Decision Making in the E-Commerce Application
Published 2024thesis::doctoral thesis -
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Modeling flood occurences using soft computing technique in southern strip of Caspian Sea Watershed
Published 2012“…Among the available learning algorithms in the Neural Network Toolbox of MATLAB, three algorithms, gradient descent back propagation (TRAINGD), gradient descent with adaptive learning rule back propagation (TRAINGDA) and the Levenberg-Marquardt (TRAINLM) were studied. …”
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DeMI interface tool for profit estimation and waste conversion technology recommendations in enhancing municipal solid waste management
Published 2024“…This state-of-the-art tool seamlessly combines process network synthesis and machine learning, using the Process Graph (P-graph) and the Waikato Environment for Knowledge Analysis (WEKA) software tools. …”
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