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Analytical Study Of Machine Learning Models For Stock Trading In Malaysian Market by Hazirah Halul

“…Therefore, this study focused to contribute on evaluating different algorithm models such as traditional ML and deep learning models with big stock data of multiple parameters from selected companies in Bursa Malaysia. …”

Evaluation of the Transfer Learning Models in Wafer Defects Classification by Jessnor Arif, Mat Jizat, Anwar, P. P. Abdul Majeed, Ahmad Fakhri, Ab. Nasir, Zahari, Taha, Yuen, Edmund, Lim, Shi Xuen

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Comparison of malware detection model using supervised machine learning algorithms / Syamir Mohd Shahirudin by Mohd Shahirudin, Syamir

“…The objective of this project is to develop the Windows malware detection model using supervised machine learning in Decision Tree, K-NN and Naïve Bayes, to evaluate the performance of malware detection in term of testing and training of the features selection and to compare the accuracy detection model in all three machine learning algorithms. …”
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Modeling time series data using Genetic Algorithm based on Backpropagation Neural network by Haviluddin

“…This study showed the task of optimizing the topology structure and the parameter values (e.g., weights) used in the BPNN learning algorithm by using the GA. Based on the results obtained, a better prediction result can be produced by the proposed GA-BPNN learning algorithm.…”
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A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment by Ruzita, Ahmad

“…The proposed algorithm is able to improve the weaknesses in PQF model in updating and learning the important attributes for software quality assessment. …”
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Evaluating machine learning algorithms for sentiment analysis: a comparative study to support data-driven decision making by Mohamad Daud, Nur Hafiza, Shafii, Nor Hayati, Md Nasir, Diana Sirmayunie, Fauzi, Nur Fatihah

“…Upon evaluating the models, the findings reveal notable differences in accuracy. …”
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Predicting building damage grade by earthquake: a Bayesian Optimization-based comparative study of machine learning algorithms by Al-Rawashdeh, Mohammad, Al Nawaiseh, Moh’d, Yousef, Isam, Bisharah, Majdi, Alkhadrawi, Sajeda, Al-Bdour, Hamza

“…This study compares Bayesian Optimization-based machine learning systems that anticipate earthquake-damaged buildings and to evaluates building damage classification models. …”
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Rabies Outbreak Prediction Using Deep Learning with Long Short-Term Memory by Abdulrazak Yahya, Saleh, Shahrulnizam, Medang, Ashraf, Osman Ibrahim

“…The performance of the proposed model is evaluated by comparing with the ARIMA model. …”
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Evaluation of machine learning algorithms in predicting CO 2 internal corrosion in oil and gas pipelines by Mohammad Zubir, W.M.A., Abdul Aziz, I., Jaafar, J.

“…It is because there are still gaps on study on evaluating suitable machine learning algorithms for corrosion prediction. …”
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Evaluation of machine learning algorithms in predicting CO2 internal corrosion in oil and gas pipelines by Mohammad Zubir, W.M.A., Abdul Aziz, I., Jaafar, J.

“…It is because there are still gaps on study on evaluating suitable machine learning algorithms for corrosion prediction. …”
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A deep reinforcement learning hybrid algorithm for the computational discovery and characterization of small proteins utilizing mycobacterium tuberculosis as a model by Ouwabunmi, Babalola AbdulHafeez

“…This study presents the development and evaluation of a novel hybrid machine learning algorithm that integrates the strengths of Random Forest and Gradient Boosting models to enhance the prediction of smORFs. …”
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Evaluation of optimal MLP structure for heart disease diagnosis / Salbiah Ab Hamid by Ab Hamid, Salbiah

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Sentiment analysis for airline services on Twitter using deep learning with word embedding / Mawada Mohamed Nour El Daim El Khalifa by Mawada Mohamed , Nour El Daim El Khalifa

“…Meanwhile, in recent years, Deep Learning algorithms for Sentiment Analysis has emerged as one of the most popular algorithms, which provides automatic feature extraction, rich representation capabilities, and better performance than most of the traditional learning algorithms. …”
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Heart Attack Prediction with Deep Learning by Syasya Putri binti Mohamad Razauddin

Edge assisted crime prediction and evaluation framework for machine learning algorithms by Adhikary, Apurba, Murad, Saydul Akbar, Munir, Md Shirajum, Choong Seon, Hong Seong

“…In particular, this study proposes a crime prediction and evaluation framework for machine learning algorithms of the network edge. …”
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Evaluations of oil palm fresh fruit bunches maturity degree using multiband spectrometer by Tuerxun, Adilijiang

“…Furthermore, the Lazy-IBK algorithm have been validated to produce the best classifier model, with the machine learning algorithm performance of 65.26%, recall of 65.3%, and 65.4% F-measured as compared to other evaluated machine learning classifier algorithms proposed within the WEKA data mining algorithm. …”
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Evaluating the Performance of a Visual Support System for Driving Assistance using a Deep Learning Algorithm by Beg, Mohammad Sojon, Muhammad Yusri, Ismail, Miah, M. Saef Ullah

“…Around one thousand images were selected in Roboflow for the train dataset. The model utilises the YOLO V8 deep learning algorithm in the Google Colab environment and is trained using a custom dataset managed by the Roboflow dataset manager. …”
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Evaluating Adan vs. Adam: an analysis of optimizer performance in deep learning by Ismail, Amelia Ritahani, Azhary, Muhammad Zulhazmi Rafiqi, Hitam, Nor Azizah

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An efficient attack detection for Intrusion Detection System (IDS) in internet of medical things smart environment with deep learning algorithm by Abdulkareem, Fatimah Saleem, Mohd Sani, Nor Fazlida

“…The CICIDS2017 dataset was used to analyze the performance of the existing intrusion detection system model. Additionally, the results of the deep learning algorithms will be evaluated using five confusion matrices, namely, accuracy, precision, recall, F1Score, and false-positive rate). …”
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Loan Eligibility Classification Using Machine Learning Approach by Law, Paul Lik Pao

“…This research was conducted using Python and Jupyter Notebook for data analysis and model development. The models were then evaluated on the testing set using evaluation metrics such as Accuracy, Precision, Recall, And F1-Score. …”
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