Search Results - (( data classification using algorithm ) OR ( using solution using algorithm ))

Dengue classification system using clonal selection algorithm / Karimah Mohd by Mohd, Karimah

“…Some of the dengue data are used to test the dengue classification system to produce the classification accuracy. …”
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Enhancing Classification Algorithms with Metaheuristic Technique by Cokro, Nurwinto, Tri Basuki, Kurniawan, Misinem, ., Tata, Sutabri, Yesi Novaria, Kunang

“…Implementing this process uses classification algorithms such asNaïve Bayes, Support Vector Machine,and Random Forest. …”
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A Hybrid of Ant Colony Optimization Algorithm and Simulated Annealing for Classification Rules by Rizauddin, Saian

“…Benchmark data sets from various fields were used to test the proposed algorithms. …”
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Weight Optimization in Recurrent Neural Networks with Hybrid Metaheuristic Cuckoo Search Techniques for Data Classification by Nawi, N.M., Khan, A., Rehman, M.Z., Chiroma, H., Herawan, T.

“…The proposed CSERN and CSBPERN algorithms are compared with artificial bee colony using BP algorithm and other hybrid variants algorithms. …”
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Logistic regression methods for classification of imbalanced data sets by Santi Puteri Rahayu, -

“…The imbalanced problem of both proposed general classification algorithms which is the limitation of accuracy performance specifically in classifying on the minority class has motivated this research to improve their classification performance on imbalanced data sets. …”
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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

“…The performance of the proposed Bat-BP algorithm is then compared with Artificial Bee Colony using BPNN (ABC-BP), Artificial Bee Colony using Levenberg-Marquardt (ABC-LM) and BPNN algorithm. …”
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Ant colony optimization algorithm for rule based classification: Issues and potential by Al-Behadili, Hayder Naser Khraibet, Ku-Mahamud, Ku Ruhana, Sagban, Rafid

“…Furthermore, this review can be used as a source of reference to other researchers in developing new ACO algorithms for rule classification.…”
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Utilizing artificial bee colony algorithm as feature selection method in Arabic text classification by Hijazi, Musab, Zeki, Akram M., Ismail, Amelia Ritahani

“…One of the widely used algorithms for feature selection in text classification is the Evolutionary algorithm . …”
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Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy by Ganesh , Krishnasamy

“…The proposed algorithm is compared with the state-of-the-art feature selection algorithms using three different datasets. …”
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Talent classification using support vector machine technique / Hamidah Jantan, Norazmah Mat Yusof and Mohd Hanapi Abdul Latif by Jantan, Hamidah, Mat Yusof, Norazmah, Abdul Latif, Mohd Hanapi

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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 performance of the proposed SCSO algorithm was compared with six state-of-the-art and recent wrapper-based optimization algorithms using the validation metrics of classification accuracy, optimum feature size, and computational cost in seconds. …”
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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

“…Water Cycle algorithm is a modern nature inspired meta-heuristic algorithm to provide derivative-free solution to optimize complex problems. …”
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Ant colony algorithm for text classification in multicore-multithread environment / Ahmad Nazmi Fadzal by Fadzal, Ahmad Nazmi

“…Pheromone concept is the main criterion that distinguish ACO to other algorithms. Based on the concept, pheromone saturation is used to combine stackable solution pattern that is discovered while straying to different term node to build a path. …”
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Abnormalities and fraud electric meter detection using hybrid support vector machine & genetic algorithm by Yap K.S., Abidin I.Z., Ahmad A.R., Hussien Z.F., Pok H.L., Ismail F.I., Mohamad A.M.

“…It provides an increased convergence and globally optimized solutions. The algorithm has been tested using actual customer consumption data from SESB. 10 fold cross validation method is used to confirm the consistency of the detection accuracy. …”

Improved cuckoo search based neural network learning algorithms for data classification by Abdullah, Abdullah

“…Specifically, 6 benchmark classification datasets are used for training the hybrid Artificial Neural Network algorithms. …”
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Gene subset selection for lung cancer classification using a multi-objective strategy by Mohamad, Mohd. Saberi, Omatu, Sigeru, Deris, Safaai, Yoshioka, Michifuci

“…It has been shown that selecting a small subset of genes can lead to improved classification accuracy. Hence, this paper proposes a solution to the problems by using a multi-objective strategy in genetic algorithms. …”
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Sentiment analysis for malay newspaper (SAMNews) using negative selection algorithm / Nur Amalina Redzuan by Redzuan, Nur Amalina

“…While in Experiment III used 900 newspaper’s sentences as the training data and 100 newspaper’s sentences as the testing data and the accuracy is unproved to 65.81%. …”
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Feature and Instances Selection for Nearest Neighbor Classification via Cooperative PSO by Sharifah Sakinah, Syed Ahmad

“…Therefore, it can be solved by using population-based techniques such as Genetic Algorithm and Particle Swarm Optimization. …”
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Spatial Clustering Algorithm for Time Series Rainfall Data Using X-Means Data Splitting by Ali, Noor Rasidah, Ku Mahamud, Ku Ruhana

“…Therefore, a clustering algorithm by introducing data transformation using X-means data splitting is proposed to investigate the spatial homogeneity of time series rainfall data. …”
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A new mobile malware classification for SMS exploitation by Zaizi N.J.M., Khailani A., Madihah Mohd Saudi

“…This research has developed a new mobile malware classification for Android smartphone using a covering algorithm. The classification has been evaluated in 500 applications and 126 applications have been identified to contain malware. � Springer International Publishing AG 2017.…”