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An improve unsupervised discretization using optimization algorithms for classification problems
Published 2024“…This paper addresses the classification problem in machine learning focusing on predicting class labels for datasets with continuous features. …”
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2
An improve unsupervised discretization using optimization algorithms for classification problems
Published 2024“…This paper addresses the classification problem in machine learning, focusing on predicting class labels for datasets with continuous features. …”
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3
Intent-IQ: customer’s reviews intent recognition using random forest algorithm
Published 2025“…Two machine learning model is chosen to build the classification models which are Random Forest (RF) algorithm and Multinomial Naïve Bayes (MNB) algorithm. …”
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4
An Empirical Evaluation of Artificial Intelligence Algorithm for Hand Posture Classification
Published 2022“…In this connection, a recent dataset, â��Mocap Hand Postures Data Set,â�� has been opted to employ the different variants of the machine learning algorithm. …”
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Development of a syncope classification algorithm from physiological signals acquired in tilt-table test
Published 2023“…Syncope also known as transient loss of consciousness which caused problem to human daily life. Since machine learning is much more advanced, classification of syncope can be done with machine learning. …”
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Final Year Project / Dissertation / Thesis -
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Recommendation System Model For Decision Making in the E-Commerce Application
Published 2024thesis::doctoral thesis -
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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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8
Modified word representation vector based scalar weight for contextual text classification
Published 2024“…For this experiment, the modified word vectors serve as input to train a Machine Learning (ML) model for the text classification process, aiming for the developed ML model to have a significantly smaller parameter count. …”
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9
Comparison on machine learning algorithm to fast detection of malicious web pages
Published 2021“…Therefore, implementing the principle of the machine learning, which is training the classification algorithm will be perform to improve the detection accuracy. …”
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Conference or Workshop Item -
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Intelligent Color Vision System For Ripeness Classification Of Oil Palm Fresh Fruit Bunch
Published 2015“…Then, the color features of the fruit region are extracted from the images and used as inputs to an Artificial Neural Network (ANN) model learning algorithm.…”
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11
Performance Review of Modern AI Algorithms Utilized for Medical Waste Sorting Works
Published 2025Conference paper -
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A COLLABORATIVE FRAMEWORK FOR ANDROID MALWARE IDENTIFICATION USING DYNAMIC ANALYSIS
Published 2019“…The Correlationbased Feature Selection Evaluator (CfsSubset) algorithm is applied in feature selection process in order to improve the classification process. …”
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Final Year Project Report / IMRAD -
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A wheelchair sitting posture detection system using pressure sensors
Published 2024“…All the classification algorithms were evaluated by using the k-fold cross validation method. …”
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Deep learning-based item classification for retail automation
Published 2025“…This project focuses on developing a deep learning-based system for retail item classification. …”
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Final Year Project / Dissertation / Thesis -
15
Systematic review for phonocardiography classification based on machine learning
Published 2023“…This systematic review aims to examine the existing literature on phonocardiography classification based on machine learning, focusing on algorithms, datasets, feature extraction methods, and classification models utilized. …”
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16
New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning
Published 2023“…A new model of stacking ensemble learning by combining three base-learner algorithms namely KNN, SVM and Random Forest into the XGBoost meta-learner algorithm. …”
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New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning
Published 2023“…A new model of stacking ensemble learning by combining three base-learner algorithms namely KNN, SVM and Random Forest into the XGBoost meta-learner algorithm. …”
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18
New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning
Published 2023“…A new model of stacking ensemble learning by combining three base-learner algorithms namely KNN, SVM and Random Forest into the XGBoost meta-learner algorithm. …”
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19
Automatic detection and indication of pallet-level tagging from rfid readings using machine learning algorithms
Published 2020“…The ensemble learning technique, changes of activation function in Neural Network as well as the unsupervised learning (k-means clustering algorithm and Friis Transmission Equation) was also applied to classify the multiclass classification in pallet-level. …”
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20
Adapting robot kinematics for human-arm motion recognition
Published 2007“…This paper presents a novel method to the analysis of human-arm motion, in particular improving the efficiency of conventional motion recognition algorithms. …”
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