Search Results - (( evolution classification mining algorithm ) OR ( _ visualization mining algorithm ))

Classification of Immunosignature Using Random Forests for Cancer Diagnosis by Zarzar, Mouayad, Razak, Eliza, Htike@Muhammad Yusof, Zaw Zaw, Yusof, Faridah

“…To attain this essential research purpose, a minimum set of genes that can assure higher performance in classification using data mining algorithms need to be detected. …”
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Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets by Saeed, Sana

“…The proposed algorithm is grounded on the two famous metaheuristic algorithms: cuckoo search (CS) and covariance matrix adaptation evolution strategy (CMA-es). …”
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Classification with degree of importance of attributes for stock market data mining by Khokhar, Rashid Hafeez, Md. Sap, Mohd. Noor

“…The SVM is a training algorithm for learning classification and regression rules from data [7]. …”
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Y-type Random 2-satisfiability In Discrete Hopfield Neural Network by Guo, Yueling

“…Additionally, the proposed Hybrid Differential Evolution Algorithm was implemented into the training phase to ensure that the cost function of the Discrete Hopfield Neural Network is minimized. …”
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Logic mining method via hybrid discrete hopfield neural network by Guo, Yueling, Mohd Kasihmuddin, Mohd Shareduwan, Zamri, Nur Ezlin, Li, Jia, Romli, Nurul Atiqah, Mansor, Mohd Asyraf, Ruzai, Wan Nur Aqlili

“…Despite the success, the limitations of existing logic mining methods are often overlooked, hindering the search for optimal solutions in binary classification tasks. …”
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A performance analysis of association rule mining algorithms by Fageeri, S.O., Ahmad, R., Alhussian, H.

“…In this paper, we evaluate the performance of association rule mining algorithms in-terms of execution times and memory usage using the CPU profiler of Java VisualVM. …”
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Algorithm Development of Bidirectional Agglomerative Hierarchical Clustering Using AVL Tree with Visualization by Hussain Mohammad Yousef Abu Dalbouh

The application of neural network data mining algorithm into mixed pixel classification in geographic information system environment by Nanna Suryana, Herman

“…However, hyperspectral image systems produce large data sets that are not easily interpretable by visual analysis and therefore require automated processing algorithm. …”
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Class binarization with self-adaptive algorithm to improve human activity recognition by Zainudin, Muhammad Noorazlan Shah

“…Therefore, feature selection using Relief-f with self-adaptive Differential Evolution (rsaDE) algorithm is proposed to select the most significant features. …”
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DATA CLASSIFICATION SYSTEM WITH FUZZY NEURAL BASED APPROACH by LUONG, TRUNG TUAN

“…The project's objective is identifying the available data mining algorithms in data classification and applying new data mining algorithm to perform classification tasks. …”
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Data mining based damage identification using imperialist competitive algorithm and artificial neural network by Gordan, Meisam, Razak, Hashim Abdul, Ismail, Zubaidah, Ghaedi, Khaled

“…In this study, to predict the damage severity of sin-gle-point damage scenarios of I-beam structures a data mining based damage identification framework and a hybrid algorithm combining Artificial Neural Network (ANN) and Imperial Competitive Algorithm (ICA), called ICA-ANN method, is proposed. …”
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Application of data mining techniques for economic evaluation of air pollution impact and control by Lukman, Iing

“…For that purpose, we use data mining techniques. Data mining techniques applied in this thesis were: 1) Group method of data handling (GMDH), originally from engineering, introducing principles of evolution - inheritance, mutation and selection - for generating a network structure systematically to develop the automatic model, synthesis, and its validation; 2) The weighted least square (WLS) and step wise regression were also applied for some cases; 3) The classification-based association rules were applied. …”
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Using text mining algorithm to detect gender deception based on Malaysian chat room lingo / Dianne L. M. Cheong and Nur Atiqah Sia Abdullah @ Sia Sze Yieng by Cheong, Dianne L.M., Sia Abdullah, Nur Atiqah

“…Based on this algorithm. a prototype in Visual Basic is developed It was tested with /6 documents; each consists of 5 e-mails exchanges of respective individuals. …”
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Using text mining algorithm to detect gender deception based on Malaysian chatroom lingo / Dianne L.M. Cheong and Nur Atiqah Sia Abdullah@Sia Sze Yieng by L., Dianne M. Cheong, Sia Abdullah, Nur Atiqah

“…Based on this designed text algorithm, a prototype in Visual Basic is developed. …”
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Classification of students' performance in computer programming course according to learning style by Norwawi N.M., Abdusalam S.F., Hibadullah C.F., Shuaibu B.M.

Enhancing predictive crime mapping model using association rule mining for geographical and demographic structure by Asmai, S. A.

“…This project proposed a data mining technique called Association Rule Mining. Basically Association Rule Mining is to investigate the rules according to the predefined parameter. …”
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Development of a new algorithm for segmentation of flotation froth images by Jahedsaravani, Ali, Marhaban, Mohammad Hamiruce, Massinaei, Mohammad, Saripan, M. Iqbal, Mehrshad, Naser, Mohd Noor, Samsul Bahari

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Comparative analysis of danger theory variants in measuring risk level for text spam messages by Zainal K., Jali M.Z., Hasan A.B.

Stock price monitoring system by Ng, Chun Ming

“…Consequently, Root Mean Squared Error (RMSE) and Mean Absolute Percentage Error (MAPE) are used to evaluate the performance of the prediction algorithms. The methodology used in this project is Cross-Industry Standard Process for Data Mining (CRISP-DM), which is a common standard for data mining projects. …”
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Exploring frogeye leaf spot disease severity in soybean through hyperspectral data analysis and machine learning with Orange Data Mining by Ang, Yuhao, Mohd Shafri, Helmi Zulhaidi, Al-Habshi, Mohammed Mustafa

“…No previous study has investigated Orange mining tool as visual programming approach in analysing hyperspectral reflectance data, especially in crop disease detection. …”
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