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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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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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Tracing active power between generators and loads for transmission open access by Zanariah Zainol

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Investigate And Analysis Of Deep Learning And Machine Learning Algorithm For Face Mask Detection System by Muhammad Ezzuddeen, Suratman

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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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Research on the construction of English intelligent classroom based on Artificial Intelligence by Wu, Yong, Othman, Abdul Jalil, Saad, Mohd Rashid Mohd

“…Though affective computing research has wide range of applications, many opening problems still exist. Due to the uncertainty of emotions, traditional machine learning algorithms may not handle this uncertain inference problem well while probability theory provides us with the basic foundation to model the uncertainty of emotions. …”
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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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Artificial Intelligence as A Common Heritage of Mankind by Wye, Dennis Keen Khong, Su, Wai Mon

“…Artificial intelligence technologies today employ techniques known as machine learning and deep learning, which apply datasets to a suitable mathematical or statistical technique known as an algorithm. …”
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Comprehensive Review of Machine Learning (ML) in Image Defogging: Taxonomy of Concepts, Scenes, Feature Extraction, and Classification techniques by Arif Z.H., Mahmoud M.A., Abdulkareem K.H., Mohammed M.A., Al-Mhiqani M.N., Mutlag A.A., Dama�evi?ius R.

AI powered asthma prediction towards treatment formulation : An android app approach by Murad, Saydul Akbar, Adhikary, Apurba, Muzahid, Abu Jafar Md, 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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Image Splicing Detection With Constrained Convolutional Neural Network by Lee, Yang Yang

“…Nowadays there are many related efforts in detecting spliced images, but most of them are either feature-specific or complicated algorithms. Constrained CNN is basically a Deep Learning CNN model with its first layer weights being constrained so that it only extracts splicing manipulation features instead of object features. …”
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Raspberry Pi-Based Finger Vein Recognition System Using PCANet by Quek, Ee Wen

“…For classification, k-Nearest Neighbours (kNN) with Euclidean distance algorithm is implemented. An enhancement version for kNN algorithm, k-General Nearest Neighbours (kGNN) have been proposed at initial stage. …”
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Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining. by Saeed, Walid

“…The accuracy for rules and classification resulted from the TIP method are compared with other methods such as Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) from Rough Set, Genetic Algorithm (GA), Johnson reducer, HoltelR method, Multiple Regression (MR), Neural Network (NN), Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5); all other classifiers that are mostly used in the classification tasks. …”
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Enhancement of neural network based multi agent system for classification and regression in energy system by Yaw C.T., Yap K.S., Wong S.Y., Yap H.J., Paw J.K.S.

Incremental learning for large-scale stream data and its application to cybersecurity by Ali, Siti Hajar Aminah

“…To process large-scale data sequences, it is important to choose a suitable learning algorithm that is capable to learn in real time. …”
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