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Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection by Saputra , Dhany, Rambli, Dayang R.A., Foong, Oi Mean

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Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

“…Using the J48 tree algorithm implemented through WEKA API on a Java Servlet, data provided is processed to derive a health index of the plant, with the possible outcomes set to “Good,” “Okay”, or “Bad”. …”
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Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things by Hadi, Ahmed Adnan

“…The experimental results showed that the accuracy of the algorithm over the NSL-KDD dataset was 99.72%, with a memory reduction of 10%. …”
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Variable step size least mean square optimization for motion artifact reduction: A review by Zailan, K.A.M., Hasan, M.H., Witjaksono, G.

“…Therefore, we propose a research to formulate an improved motion artifact reduction approach using variable step-size least mean square (VSSLMS). …”
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Applying machine learning and particle swarm optimization for predictive modeling and cost optimization in construction project management by almahameed, Bader aldeen, Bisharah, Majdi

“…Particle Swarm Optimization (PSO) has demonstrated its efficacy in addressing the issue of construction waste reduction and enhancing the accuracy of cost estimation through the identification of optimal combinations of variables. …”
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Mining Sequential Patterns using I-PrefixSpan by Saputra , Dhany, Dayang R.A. Rambli, Foong, Oi Mean

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Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde by Ogunfolajin Maruff , Tunde

“…This thesis is based on the application of sentiment classification algorithm to tweet data with the goal of classifying messages based on the polarity of sentiment towards a particular topic (or subject matter). …”
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A hybridisation of adaptive variable neighbourhood search and large neighbourhood search: Application to the vehicle routing problem by Sze, Jeeu Fong, Salhi, S., Wassan, N.

“…In this paper, an adaptive variable neighbourhood search (AVNS) algorithm that incorporates large neighbourhood search (LNS) as a diversification strategy is proposed and applied to the capacitated vehicle routing problem. …”
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Mining Sequential Patterns Using I-PrefixSpan by Dhany , Saputra, Rambli Dayang, R.A., Foong, Oi Mean

“…In this paper, we propose an improvement of pattern growth-based PrefixSpan algorithm, called I-PrefixSpan. The general idea of I-PrefixSpan is to use the efficient data structure for general tree-like framework and separator database to reduce the execution time and memory usage. …”
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Cleansing of inconsistent sample in linear regression model based on rough sets theory by Rasyidah, Rasyidah, Efendi, Riswan, Mohd. Nawi, Nazri, Mat Derisf, Mustafa, Aqil Burney, S.M.

“…The linear regression model is one of the most common and easiest algorithms used in machine learning for predictive analysis purposes. …”
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Cleansing of inconsistent sample in linear regression model based on rough sets theory by Rasyidah, Rasyidah, Efendi, Riswan, Mohd. Nawi, Nazri, Mat Deris, Mustafa, Burney, S.M.Aqil

“…The linear regression model is one of the most common and easiest algorithms used in machine learning for predictive analysis purposes. …”
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Cleansing of inconsistent sample in linear regression model based on rough sets theory by Rasyidah, Rasyidah, Efendi, Riswan, Mohd. Nawi, Nazri, Mat Deris, Mustafa, Aqil Burney, S.M.

“…The linear regression model is one of the most common and easiest algorithms used in machine learning for predictive analysis purposes. …”
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Cleansing of inconsistent sample in linear regression model based on rough sets theory by Rasyidah, Rasyidah, Riswan Efendi, Riswan Efendi, Mohd. Nawi, Nazri, Mat Deris, Mustafa, Aqil Burney, S.M.

“…The linear regression model is one of the most common and easiest algorithms used in machine learning for predictive analysis purposes. …”
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AI powered asthma prediction towards treatment formulation: an android app approach by Murad, Saydul Akbar, Adhikary, Apurba, Md Muzahid, Abu Jafar, Sarker, Md Murad Hossain, Khan, Md. Ashikur Rahman, Hossain, Md. Bipul, Bairagi, Anupam Kumar, Masud, Mehedi, Kowsher, Md

“…We utilized eight robust machine learning algorithms to analyze this dataset. We found that the Decision tree classifier had the best performance, out of the eight algorithms, with an accuracy of 87%. …”
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Reinforcement learning-based target tracking for unmanned aerial vehicle with achievement rewarding and multistage traning by Ahmed Abo Mosali, Najm Addin Mohammed

“…In this thesis, the Twin Delayed Deep Deterministic Policy Gradient Algorithm (TD3), as one recent and composite architecture of reinforcement learning (RL), has been explored as a tracking agent for the problem of UAV-based target tracking. …”
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Cleansing of inconsistent sample in linear regression model based on rough sets theory by Rasyidah, Rasyidah, Riswan Efendi, Riswan Efendi, Nazri Mohd. Nawi, Nazri Mohd. Nawi, Mustafa Mat Deris, Mustafa Mat Deris, S.M.Aqil Burney, S.M.Aqil Burney

“…The linear regression model is one of the most common and easiest algorithms used in machine learning for predictive analysis purposes. …”
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Cleansing of inconsistent sample in linear regression model based on rough sets theory by Rasyidah, Rasyidah, Efendi, Riswan, Mohd. Nawi, Nazri, Mat Deris, Mustafa, S.M.Aqil Burney, S.M.Aqil Burney

“…The linear regression model is one of the most common and easiest algorithms used in machine learning for predictive analysis purposes. …”
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Cleansing of inconsistent sample in linear regression model based on rough sets theory by Rasyidah, Rasyidah, Efendi, Riswan, Mohd. Nawi, Nazri, Mat Deris, Mustafa, S.M.Aqil Burney, S.M.Aqil Burney

“…The linear regression model is one of the most common and easiest algorithms used in machine learning for predictive analysis purposes. …”
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Cleansing of inconsistent sample in linear regression model based on rough sets theory by Rasyidah, Rasyidah, Efend, Riswan, Mohd. Nawi, Nazri, Mat Derisf, Mustafa, S.M.Aqil Burney, S.M.Aqil Burney

“…The linear regression model is one of the most common and easiest algorithms used in machine learning for predictive analysis purposes. …”
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Cleansing of inconsistent sample in linear regression model based on rough sets theory by Rasyidah, Rasyidah, Efendi, Riswan, Mohd. Nawi, Nazri, Mat Deris, Mustafa, S.M.Aqil Burney, S.M.Aqil Burney

“…The linear regression model is one of the most common and easiest algorithms used in machine learning for predictive analysis purposes. …”
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