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Crytojacking Classification based on Machine Learning Algorithm by Mansor W.N.A.B.W., Ahmad A., Zainudin W.S., Kama M.N., Madihah Mohd Saudi

A novel framework for identifying twitter spam data using machine learning algorithms by Maziku, Susana Boniphace, Abdul Rahiman, Amir Rizaan, Muhammed, Abdullah, Abdullah @ Selimun, Mohd Taufik

“…The research results contribute significantly to the field of cyber-security by forming a real-time system using machine learning algorithms.…”
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An experimental evaluation of case slicing as a new classification technique by Shiba, Omar A. A., Sulaiman, Md. Nasir, Ahmad, Fatimah, Mamat, Ali

“…Lastly, it compares the proposed approach with other selected approaches such as the K-Nearest Neighbour (K-NN), Base Learning Algorithm (C4.5) and Naïve Bayes classifier (NB) in solving the classification problems. …”
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A conceptual model for the E-commerce application recommendation framework using exploratory search by Mohammed Mahmudur Rahman, Zulkifly Mohd Zaki, Md. Monirul Islam, Najwa Hayaati Mohd Alwi

Semi-supervised learning for sentiment classification with ensemble multi-classifier approach by Aribowo, Agus Sasmito, Basiron, Halizah, Abd Yusof, Noor Fazilla

“…The conclusion is that the sentiment annotation accuracy is highly dependent on the suitability of the dataset with the machine learning algorithm. In IMDB dataset, which consists of two classes, it is better to use SVM. …”
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A Machine Learning Classification Approach to Detect TLS-based Malware using Entropy-based Flow Set Features by Keshkeh, Kinan, Jantan, Aman, Alieyan, Kamal

“…Due to the complexity of TLS traffic decryption, several anomaly-based detection studies have been conducted to detect TLS-based malware using different features and machine learning (ML) algorithms. However, most of these studies utilized flow features with no feature transformation or relied on inefficient flow feature transformations like frequency-based periodicity analysis and outliers percentage. …”
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Sarcasm detection in Persian by Nezhad, Zahra Bokaee, Deihimi, Mohammad Ali

“…The performance of the model is analysed using several standard machine learning algorithms. The results of the experiment showed that the method outperformed the baseline method and reached an accuracy of 80.82%. …”
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Pattern generation through feature values modification and decision tree ensemble construction by Akhand, M. A. H, Rahman, M.M. Hafizur, Murase, K.

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Semantic focus fusion based on deep learning for deblurring effect by Ismail, .

“…In a rapid development of intelligent computation, such as deep learning algorithm, multi-focus image fusion methods indirectly being involved, such as CNN and PCA Net architectures. …”
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Case Slicing Technique for Feature Selection by A. Shiba, Omar A.

“…One of the problems addressed by machine learning is data classification. Finding a good classification algorithm is an important component of many data mining projects. …”
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Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model by Sulaiman, Md. Nasir, Mohamed, Raihani, Mustapha, Norwati, Zainudin, Muhammad Noorazlan Shah

“…Hence, this situation is believed in yielding of decreasing the classification accuracy. In this article, we present the exploration on the combination of the clustering based algorithm with an ensemble classification learning. …”
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Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition by Leong, Shi Xiang

“…The problems in applying unsupervised learning/clustering is that this method requires teacher during the classification process and it has to learn independently which may lead to poor classification. …”
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Functional link neural network with modified bee-firefly learning algorithm for classification task by Mohmad Hassim, Yana Mazwin

“…The aim is to introduce an improved learning algorithm that can provide a better solution for training the FLNN network for the task of classification…”
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Phylogenetic tree classification system using machine learning algorithm by Tan, Jia Kae

“…This study adopted supervised machine learning algorithm which is the Support Vector Machine (SVM) for classification. …”
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Autism Spectrum Disorder Classification Using Deep Learning by Abdulrazak Yahya, Saleh, Lim Huey, Chern

“…The goal of this paper is to evaluate the deep learning algorithm for people placed in the Autism Spectrum Disorder (ASD) classification. …”
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Using KNN algorithm for classification of textual documents by Moldagulova A., Sulaiman R.B.

“…Classification (of information); Information retrieval systems; Learning systems; Nearest neighbor search; Tellurium compounds; Text processing; Automated classification; Exponential growth; K nearest neighbor (KNN); k-NN algorithm; Text classification; Textual documents; Two sources; Learning algorithms…”

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

“…Transfer Learning is one of the common methods. Various algorithms under Transfer Learning had been developed for different applications. …”
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Grid-Based Classifier as a Replacement for Multiclass Classifier in a Supervised Non-Parametric Approach by Moheb Pour, Majid Reza

“…The two algorithms were compared, and the proposed algorithm was found to be able to both learn and classify quickly. …”
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Waste management using machine learning and deep learning algorithms by Sami, Khan Nasik, Amin, Zian Md Afique, Hassan, Raini

“…So, we are proposing an automated waste classification problem utilizing Machine Learning and Deep Learning algorithms. …”
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A Comparative Analysis of Machine Learning and Deep Learning Algorithms for Image Classification by Madanan M., Gunasekaran S.S., Mahmoud M.A.

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