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Building classification models from imbalanced fraud detection data / Terence Yong Koon Beh, Swee Chuan Tan and Hwee Theng Yeo by Terence, Yong Koon Beh, Swee, Chuan Tan, Hwee, Theng Yeo

“…When the data is imbalanced, these algorithms generate models that achieve good classification accuracy for the majority class, but poor accuracy for the minority class. …”
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Mobile machine vision for railway surveillance system using deep learning algorithm by Kit, Guan Lim, Daniel Siruno, Min, Keng Tan, Chung, Fan Liau, Sha, Huang, Tze, Kenneth Kin Teo

“…In this paper, object detection model is developed and implemented with deep learning algorithm. …”
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Development of classification algorithms of human gait by Koh, Chee Hong

“…Two classification algorithms were developed: Support Vector Machine (SVM) classification algorithm and Artifical Neural Network (ANN). …”
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Support directional shifting vector: A direction based machine learning classifier by Kowsher, Md., Hossen, Imran, Tahabilder, Anik, Prottasha, Nusrat Jahan, Habib, Kaiser, Zafril Rizal, M Azmi

“…In this article, we have focused on developing a model of angular nature that performs supervised classification. …”
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Using genetic algorithms to optimise land use suitability by Pormanafi, Saeid

“…In this study, under environmentfriendliness objective, based on multi-agent genetic algorithms, was developed a geospatial model for the land use allocation. …”
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Predicting attackers of online shaming using ant colony optimization / Noor Shafiqa Fazlien Mohamad Fauzi by Mohamad Fauzi, Noor Shafiqa Fazlien

“…The main objective of this study is to develop a class model for predicting the attackers of online shaming. …”
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A novel hybrid classification model of genetic algorithms, modified k-Nearest Neighbor and developed backpropagation neural network by Salari, Nader, Shohaimi, Shamarina, Najafi, Farid, Nallappan, Meenakshii, Karishnarajah, Isthrinayagy

“…To develop proposed model, with the aim of obtaining the best array of features, first, feature ranking techniques such as the Fisher's discriminant ratio and class separability criteria were used to prioritize features. …”
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An improved vulnerability exploitation prediction model with novel cost function and custom trained word vector embedding by Hoque M.S., Jamil N., Amin N., Lam K.-Y.

Sentiment analysis on airline reviews using Naive Bayes / Nurul Sarah Aliessa Che Harun by Che Harun, Nurul Sarah Aliessa

“…In order to tackle class imbalance in the dataset, ADASYN oversampling was done and then, afterward, the model turned to more reliable regarding detecting positive and negative sentiments. …”
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A Reinforced Active Learning Algorithm for Semantic Segmentation in Complex Imaging by Usmani, U.A., Watada, J., Jaafar, J., Aziz, I.A., Roy, A.

“…Semantic segmentation annotation helps train computer vision based Artificial Intelligence models where each image pixel is assigned to a specific object class. …”
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SMALL-SCALE PRIMARY SCHOOL TIMETABLING PROBLEM by Yong, Phang How

“…The main objective of this study is to propose a two-staged heuristic solution for Primary School Timetabling whereby the algorithm should enable combination of classes from different classes of students and reduce the number of subjects to be taught in a day and develop a simulation model for Primary School Timetabling Problem. …”
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Quality of service management algorithms in WiMAX networks by Saidu, Ibrahim

“…In addition, an analytical model for the proposed scheme is developed. Secondly, a Load-Aware Weighted Round Robin algorithm (LAWRR) packet scheduling discipline for downlink traffic in 802.16 networks is proposed to improve the poor performance of scheduling algorithm that use static weights under bursty traffic. …”
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A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption by Nurnajmin Qasrina Ann, Ayop Azmi

“…The research starts with developing the hybrid deep learning model consisting of DNN and a K-Means Clustering Algorithm. …”
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Classification of imbalanced travel mode choice to work data using adjustable svm model by Qian, Y., Aghaabbasi, M., Ali, M., Alqurashi, M., Salah, B., Zainol, R., Moeinaddini, M., Hussein, E.E.

“…This study deals with imbalanced mode choice data by developing an algorithm (SVMAK) based on a support vector machine model and the theory of adjusting kernel scaling. …”
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SOMEA: self-organizing map based extraction algorithm for DNA motif identification with heterogeneous model by Lee, Nung Kion, Wang, Dianhui

“…Conclusions: Motif discovery with model based clustering framework should consider the use of heterogeneous model to represent the two classes of signals in DNA sequences. …”
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A Voting Technique Of Multilayer Perceptron Ensemble For Classification Application by Talib, Hafizah

“…In this research, an integrated system of Multi-Layer Perceptron Ensemble (MLPE) consisting of an MLPE and a new voting algorithm has been developed to increase classification accuracy and reduce the number of reject class cases. …”
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A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem by Mohd Pozi, Muhammad Syafiq

“…Hence, a biased classification model is highly anticipated as higher accuracy can always be represented by majority class. …”
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Student-Class (SC) optimization system / Haifaa Mahfuzah Hazalin by Hazalin, Haifaa Mahfuzah

“…To solve the issue the Student-Class Optimization System had been developed by using optimization technique, specifically, is a Greedy Algorithm. …”
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The compact genetic algorithm for likelihood estimator of first order moving average model by Al-Dabbagh, R.D., Baba, M.S., Mekhilef, Saad, Kinsheel, A.

“…The poor behavior of genetic algorithms in some problems, sometimes attributed to design operators, has led to the development of other types of algorithms. …”
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SVM for network anomaly detection using ACO feature subset by Mehmood, T., Rais, H.B.M.

“…Classification approach has been widely adopted for the development of the anomaly detection model to classify the data into normal class and attack class. …”
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