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Intent-IQ: customer’s reviews intent recognition using random forest algorithm by Mazlan, Nur Farahnisrin, Ibrahim Teo, Noor Hasimah

“…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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Analysis on The Prediction of Homeless using Machine Learning Algorithm by Mohd Burhan, Nur Izza Natilia

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Waste management using machine learning and deep learning algorithms by Sami, Khan Nasik, Amin, Zian Md Afique, Hassan, Raini

“…For our research we did the comparisons between three Machine Learning algorithms, namely Support Vector Machine (SVM), Random Forest, and Decision Tree, and one Deep Learning algorithm called Convolutional Neural Network (CNN), to find the optimal algorithm that best fits for the waste classification solution. …”
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The forecasting of poverty using the ensemble learning classification methods by Zamzuri, Muhammad Haziq Adli, Nadilah, Sofian, Hassan, Raini

“…Random Forest and Extreme Gradient Boosting (XGBoost) algorithms were applied to forecast poverty since they are supervised learning algorithms that use the ensemble learning approach for classification. …”
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Developing framework for natphoric computer-aided web-based kansei engineering / Mohammad Bakri Che Haron by Che Haron, Mohammad Bakri

“…The Natphoric algorithm learns the process done by training with sets of training data from previous KE research works. …”
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Customer behavior analysis based on purchasing history and reviews using automated decision-making systems by Allur, Naga Sushma, Deevi, Durga Praveen, Dondapati, Koteswararao, Chetlapalli, Himabindu, Kodadi, Sharadha, Perumal, Thinagaran

“…Techniques: Then, the decision-making process is used to analyze the customer’s data using the regression algorithm. Result: This results in the proposed model, the relationship of the many business models, the formation of the purchases that affect consumer needs, and the strategies that can be developed. …”
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Early bacterial detection in bloodstream infection using deep transfer learning algorithm by Son Ali, Akbar, Kamarul Hawari, Ghazali, Habsah, Hasan, Wahyu Sapto, Aji, Yudhana, Anton

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Educational video recommender system for computer science students using content-based filtering / Walid Burhani Mohd Zamani by Mohd Zamani, Walid Burhani

“…The problem is the student finds it hard to find suitable educational videos that suit their interest, and students get time consuming when searching for educational videos. The objective is to study the content-based algorithm, to develop the prototype of educational video recommendation system using content-based filtering algorithm and to evaluate the performance and accuracy of the content-based filtering algorithm. …”
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Kernel and multi-class classifiers for multi-floor wlan localisation by Abd Rahman, Mohd Amiruddin

“…Unlike the classical kNN algorithm which is a regression type algorithm, the proposed localisation algorithms utilise machine learning classification for both linear and kernel types. …”
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Analysis of online CSR message authenticity on consumer purchase intention in social media on Internet platform via PSO-1DCNN algorithm by Li, Man, Liu, Fang, Abdullah, Zulhamri

“…Secondly, this work designs optimization measures from inertia weight and learning factor to build an improved particle swarm optimization algorithm (IPSO). …”
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Recent Automatic Segmentation Algorithms of MRI Prostate Regions: A Review by Khan, Z., Yahya, N., Alsaih, K., Al-Hiyali, M.I., Meriaudeau, F.

“…This survey reviewed 22 machine learning and 88 deep learning-based segmentation of prostate MRI papers, including all MRI modalities. …”
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Recent Automatic Segmentation Algorithms of MRI Prostate Regions: A Review by Khan, Z., Yahya, N., Alsaih, K., Al-Hiyali, M.I., Meriaudeau, F.

“…This survey reviewed 22 machine learning and 88 deep learning-based segmentation of prostate MRI papers, including all MRI modalities. …”
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Enhanced human activity recognition framework for wearable devices based on explainable AI by Perumal, Thinagaran, Yumeng, Xie, Chengzhi, Liu, Cheng, Jing

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Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy by Ganesh , Krishnasamy

“…An efficient iterative algorithm is developed to optimize the objective function of the proposed algorithm since it is non-smooth and difficult to solve. …”
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Predictive modelling of nanofluids thermophysical properties using machine learning by Olanrewaju, Alade Ibrahim

“…This thesis aimed to develop machine learning algorithms to estimate the thermophysical properties of commonly used nanofluids. …”
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Brain tumor image segmentation using deep learning approach by Darshan, Suresh

“…Deep learning algorithm is able to provide good tumor segmentation results compared to other conventional segmentation algorithms as it learns from the labeled brain MRIs to predict the location of tumor region and consequently segment the tumor. …”
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Machine learning approach for automated optical inspection of electronic components by Lim, Siew Kee

“…The factor that affecting the confidence level of the supervised machine learning algorithm is discussed. …”
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Context-Aware Recommender System based on machine learning in tourist mobile application / Nor Liza Saad … [et al.] by Saad, Nor Liza, Khairudin, Nurkhairizan, Azizan, Azilawati, Abd Rahman, Abdullah Sani, Ibrahim, Roslina

“…The objective of this research is to develop a tourist mobile application that can be incorporated with machine learning based recommender system. …”
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A protocol for developing a classification system of mosquitoes using transfer learning by Pradeep Isawasan, Zetty Ilham Abdullah, Ong, Song Quan, Khairulliza Ahmad Salleh

“…This protocol aims to develop step-by-step procedure in developing a classification system with transfer learning algorithm for mosquito, we demonstrate the protocol to classify two species of Aedes mosquito - Aedes aegypti L. and Aedes albopitus L, but user can adopt the protocol for higher number of species classification. …”
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Decision tree and rule-based classification for predicting online purchase behavior in Malaysia / Maslina Abdul Aziz, Nurul Ain Mustakim and Shuzlina Abdul Rahman by Abdul Aziz, Maslina, Mustakim, Nurul Ain, Abdul Rahman, Shuzlina

“…The performance of six machine learning models comprising J48, Random Tree, REPTree representing decision trees and JRip, PART, and OneR as rule-based algorithms was assessed. …”
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