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Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly
Published 2019“…This project will use fuzzy k-means clustering algorithm to cluster the data because it is easy to implement and have many advantages. …”
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Thesis -
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Prediction of Machine Failure by Using Machine Learning Algorithm
Published 2019“…Then, the data is cluster by using K Means to produce labeled input that will be trained by using Gradient Boosting Machine, a decision tree algorithm to make prediction. …”
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Final Year Project -
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Development of Machine Learning Algorithm for Acquiring Machining Data in Turning Process
Published 2004“…The most widely used source of such data is the Machining Data Handbook (MDH) published by Metcut Research Association, (1980). …”
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4
Mapping the distribution of oil palm using Landsat 8 data by comparing machine learning and non-machine learning algorithms
Published 2019“…Landsat 8 images of resolutions 15 x 15 m were used and classified via machine learning and non-machine learning algorithms. …”
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Octane number prediction for gasoline blends using convolution neural network / Zhu Yue
Published 2021“…Machine performance learning models depend to a large extant to the data quality used train the model. …”
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6
Comparative study of machine learning algorithms in data classification
Published 2025“…The results will help with real-world data mining applications of machine learning and be a useful guide for further study and practical applications.…”
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Final Year Project / Dissertation / Thesis -
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Comparison of malware detection model using supervised machine learning algorithms / Syamir Mohd Shahirudin
Published 2022“…Then, the outcomes demonstrated that the best classifier for categorizing our data with 0.96% accuracy is the Decision Tree machine learning algorithm. …”
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Student Project -
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Performances of machine learning algorithms for binary classification of network anomaly detection system
Published 2018“…The aim of this paper to build a network anomaly detection system using machine learning algorithms that are efficient, effective and fast processing. …”
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A case study of microarray breast cancer classification using machine learning algorithms with grid search cross validation
Published 2023“…In this work, simple machine learning methods are used to classify breast cancer microarray data to normal and relapse. …”
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Optimal route checking using genetic algorithm for UiTM's bus services / Tengku Salman Fathi Tengku Jaafar
Published 2006“…Although from human logical thinking, the route can be generated easily but the calculation of checking the route whether it is optimal route or not is difficult and will take long time to be implemented. This research study with the development of the Optimal Route Checking Using Genetic Algorithm system should solve this scenario. …”
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12
Comparative performance of deep learning and machine learning algorithms on imbalanced handwritten data
Published 2018“…The experiment shows that although the algorithm is stable and suitable for multiple domains, the imbalanced data distribution still manages to affect the outcome of the conventional machine learning algorithms.…”
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A comparative analysis of predicting heart disease using machine learning algorithms
Published 2026“…The purpose of this study is to investigate the potential of machine learning algorithms in forecasting heart disease and compare the performance of each algorithm. …”
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Privacy Preserving Features Selection for Data Mining using Machine Learning Algorithms
Published 2023Conference Paper -
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Classification of fault and stray gassing in transformer by using duval pentagon and machine learning algorithms
Published 2022“…Data resampling technique (SMOTETomek) is applied and shows further improvement on the accuracy of predictions by machine learning algorithms when deal with imbalance data. …”
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An optimized variant of machine learning algorithm for datadriven electrical energy efficiency management (D2EEM)
Published 2024“…The scope of this study is tri folded, First, an exhaustive and parametric comparative study on a wide variety of machine learning algorithms is presented to evaluate the performance of machine learning algorithms in energy load prediction. …”
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Thesis -
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E4ML: Educational Tool for Machine Learning
Published 2003“…There are various types of machine learning algorithms with certain processes taken by the algorithm.In teaching of the machine learning algorithms, such processes need to be explained especially to the beginner in introductory level.This paper discusses the development the tool that addresses the process by certain algorithm to produce a hypothesis or output based on given data.This tool can also be used in teaching and learning purposes.The explanation of processes by the algorithms is demonstrated through simple simulation.The source of the algorithms was adapted from Mitchell book [1] that cover popular algorithms in machine learning for teaching and learning such as Concept Learning, Decision Tree, Bayesian Learning, Neural Networks, and Instance based Learning.The tool also used several classes of Weka (Waikato Environment for Knowledge Analysis) as a basis for the design and implementation of the new tool that focuses on explaining the processes taken by certain algorithm.…”
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Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde
Published 2022“…Thus, there is a need to automate the process of identifying and predicting (positive, negative, or neutral class) these cyber-trooping data. This work employed the use of machine learning approach. …”
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Stock Price Prediction Analysis Dashboard using Machine Learning with LSTM Neural Network
Published 2021“…Machine Learning (ML) is a method of studying the computer algorithms that can improve and advance automatically throughout time with experience by using data that is collected by humans. …”
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Final Year Project -
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BASE: a bacteria foraging algorithm for cell formation with sequence data
Published 2010“…The performance of the proposed algorithm is compared with that of a number of algorithms that are most commonly used and reported in the corresponding scientific literature, such as the CASE clustering algorithm for sequence data, the ACCORD bicriterion clustering algorithm and modified ART1, and using a defined performance measure known as group technology efficiency and bond efficiency. …”
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