Search Results - (( based simulation based algorithm ) OR ( data classification learning algorithm ))

WCBP: A new water cycle based back propagation algorithm for data classification by Mohd. Nawi, Nazri, Khan, Abdullah, Firdaus, Naim, M. Z., Rehman, Siming, Insaf Ali

“…The performance of the proposed Water Cycle based Back-Propagation (WCBP) algorithm is compared with the conventional BPNN, ABC-BP and ABC-LM algorithms on selected benchmark classification problems from UCI Machine Learning Repository. …”
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BAT-BP: A new BAT based back-propagation algorithm for efficient data classification by Mohd. Nawi, Nazri, M. Z., Rehman, Hafifi, Nurfarian, Khan, Abdullah, Siming, Insaf Ali

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Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets by Saeed, Sana

“…Classification of imbalanced datasets remained a significant issue in data mining and machine learning (ML) fields. …”
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Diabetes Diagnosis And Level Of Care Fuzzy Rule-Based Model Utilizing Supervised Machine Learning For Classification And Prediction by Mohd Aris, Teh Noranis, Abu Bakar, Azuraliza, Mahiddin, Normadiah, Zolkepli, Maslina

“…Therefore, a fuzzy model based on machine learning and data mining is a vital solution. …”
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Improved cuckoo search based neural network learning algorithms for data classification by Abdullah, Abdullah

“…On the other hand, LM algorithms which are derivative based algorithms still face a risk of getting stuck in local minima. …”
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A Novel Wrapper-Based Optimization Algorithm for the Feature Selection and Classification by Talpur, N., Abdulkadir, S.J., Hasan, M.H., Alhussian, H., Alwadain, A.

“…The simulation results on the benchmark medical datasets revealed that the proposed SCSO-KNN approach has outperformed comparative algorithms with an average classification accuracy of 93.96 by selecting 14.2 features within 1.91 s. …”
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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 comparative study and simulation of object tracking algorithms by Ji, Yuanfa, Yin, Pan, Sun, Xiyan, Kamarul Hawari, Ghazali, Guo, Ning

“…This article introduces the popular object tracking algorithms, from common problems in object tracking to the classification of algorithms: Early classic trackingalgorithms, tracking algorithms based on kernel correlation filtering, and tracking algorithms based on deep learning. …”
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A class skew-insensitive ACO-based decision tree algorithm for imbalanced data sets by Mohd Razali, Muhamad Hasbullah, Saian, Rizauddin, Yap, Bee Wah, Ku-Mahamud, Ku Ruhana

“…This study proposed an enhanced algorithm called hellingerant-tree-miner (HATM) which is inspired by ant colony optimization (ACO) metaheuristic for imbalanced learning using decision tree classification algorithm. …”
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Optimal Weighted Learning of PCA and PLS for Multicollinearity Discriminators and Imbalanced Groups in Big Data (S/O: 13224) by Mahat, Nor Idayu, Engku Abu Bakar, Engku Muhammad Nazri, Zakaria, Ammar, Mohd Nazir, Mohd Amril Nurman, Misiran, Masnita

“…This study developed an algorithm for statistical classification that enable ones to classify a future data to one of predetermined groups based on the measured data which facing two major threats; (i) multicollinearity among the measured variables and (ii) imbalanced groups. …”
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The classification of wink-based eeg signals by means of transfer learning models by Jothi Letchumy, Mahendra Kumar

“…Hitherto, limited studies have investigated the classification of wink-based EEG signals through TL accompanied by classical Machine Learning (ML) pipelines. …”
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The impact of fuzzy discretization�s output on classification accuracy of random forest classifier by Fikri, M.N., Hassan, M.F., Tran, D.C.

“…Random Forest is known as among the widely used classification algorithms by researchers and machine learning enthusiast in solving classification problems. …”
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Deep learning-based item classification for retail automation by Ling, Ji Xiang

“…This project focuses on developing a deep learning-based system for retail item classification. …”
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Fault classification in smart distribution network using support vector machine by Chuan O.W., Ab Aziz N.F., Yasin Z.M., Salim N.A., Wahab N.A.

“…In this paper, a machine-learning algorithm known as Support Vector Machine (SVM) for fault type classification in distribution system has been developed. …”

Cyberbullying detection: a machine learning approach by Yeong, Su Yen

“…This model combines a rule-based approach of sentiment analysis and a supervised machine learning algorithm to classify the text. …”
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Simultaneous fault diagnosis based on multiple kernel support vector machine in nonlinear dynamic distillation column by Taqvi, S.A.A., Zabiri, H., Uddin, F., Naqvi, M., Tufa, L.D., Kazmi, M., Rubab, S., Naqvi, S.R., Maulud, A.S.

“…In the developed MK-SVM algorithm, multilabel approach based on various kernel functions has been utilized for the classification of simultaneous faults. …”
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An application of artificial neural network classifier for medical diagnosis by Khaleel Ibraheem, Amjed

“…Simulation results proved the ability of ANN for medical data classification with high accuracy and excellent performance and efficiency. …”
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Plant recognition based on identification of leaf image using image processing / Nor Silawati Sha’ari by Sha’ari, Nor Silawati

“…In this paper, by using the database available in the internet and using Neural Network (NN) as training algorithm, plant recognition based on leaves image would be developed. …”
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A voting-based hybrid machine learning approach for fraudulent financial data classification / Kuldeep Kaur Ragbir Singh by Kuldeep Kaur , Ragbir Singh

“…To bridge this gap, this research embarks on developing a hybrid machine learning approach to identify credit card fraud cases based on both benchmark and real-world data. Standard base machine learning algorithms, which include a total of twelve individual methods as well as the AdaBoost and Bagging methods, are firstly used. …”
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Prognostic Health Management of Pumps Using Artificial Intelligence in the Oil and Gas Sector: A Review by Aliyu, R., Mokhtar, A.A., Hussin, H.

“…To further understand its potential, various algorithms and related theories are examined. Based on the examined studies, machine learning shows potential for prognostics and defect diagnosis. …”
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