Search Results - (( simulation classification _ algorithm ) OR ( variable learning based algorithm ))

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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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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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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Information Theoretic-based Feature Selection for Machine Learning by Muhammad Aliyu, Sulaiman

“…Three major factors that determine the performance of a machine learning are the choice of a representative set of features, choosing a suitable machine learning algorithm and the right selection of the training parameters for a specified machine learning algorithm. …”
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Permodelan Rangkaian Neural Buatan Untuk Penilaian Kendiri Teknologi Maklumat Guru Pelatih by Hashim, Asman

“…The research procedures chosen were the multi-layered perceptron with back propagation algorithmic learning. The research findings show that the most suitable predictive model comprises of eleven nodes in input-layer; five nodes in hidden-layer and one node in output-layer. …”
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Feature Selection using Binary Simulated Kalman Filter for Peak Classification of EEG Signals by Badaruddin, Muhammad, Mohd Falfazli, Mat Jusof, Mohd Ibrahim, Shapiai, Asrul, Adam, Zulkifli, Md. Yusof, Kamil Zakwan, Mohd Azmi, Nor Hidayati, Abdul Aziz, Zuwairie, Ibrahim, Norrima, Mokhtar

“…Previously, an angle modulated simulated Kalman filter (AMSKF) algorithm has been implemented for feature selection in peak classification of electroencephalogram (EEG) signals. …”
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A Hybrid of Ant Colony Optimization Algorithm and Simulated Annealing for Classification Rules by Rizauddin, Saian

“…Thus, this thesis proposed two variants of hybrid ACO with simulated annealing (SA) algorithm for solving problem of classification rule induction. …”
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Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets by Saeed, Sana

“…For its fast convergence and for its efficient search procedure, the self-adaptation is proposed in the parameters of the proposed hybrid algorithm. The effectiveness of this algorithm is verified by applying it on the unconstrained and constrained test functions through a simulation study. …”
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Selection and optimization of peak features for event-related eeg signals classification / Asrul bin Adam by Asrul, Adam

“…At first, a peak classification algorithm is developed based on the general following processes including peak candidate identification, feature extraction, and classification. …”
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Ant colony optimization for rule induction with simulated annealing for terms selection by Saian, Rizauddin, Ku-Mahamud, Ku Ruhana

“…This paper proposes a sequential covering based algorithm that uses an ant colony optimization algorithm to directly extract classification rules from the data set.The proposed algorithm uses a Simulated Annealing algorithm to optimize terms selection, while growing a rule.The proposed algorithm minimizes the problem of a low quality discovered rule by an ant in a colony, where the rule discovered by an ant is not the best quality rule, by optimizing the terms selection in rule construction. …”
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An improved pixel-based and region-based approach for urban growth classification algorithms / Nur Laila Ab Ghani by Ab Ghani, Nur Laila

“…The improved algorithm is constructed by adding new parameter and classification rule to existing algorithm. …”
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Classification for large number of variables with two imbalanced groups by Ahmad Hakiim, Jamaluddin

“…This study proposed two algorithms of classification namely Algorithm 1 and Algorithm 2 which combine resampling, variable extraction, and classification procedure. …”
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Ensemble-based machine learning algorithms for classifying breast tissue based on electrical impedance spectroscopy by Rahman, Sam Matiur, Ali, Md. Asraf, Altwijri, Omar, Alqahtani, Mahdi, Ahmed, Nasim, Ahamed, Nizam Uddin

“…In addition, the ranked order of the variables based on their importance differed across the ML algorithms. …”
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An Analysis Of Various Algorithms For Text Spam Classification And Clustering Using Rapidminer And Weka by Zainal K., Sulaiman N.F., Jali M.Z.

“…By using the same dataset, which is downloaded from UCI, Machine Learning Repository, various algorithms used in classification and clustering in this simulation has been analysed comparatively. …”

Accuracy assessment of Digital Terrain Model (DTM) Constructed Cloth Simulation Filter (CSF) and Multi Curvature Classification (MCC) algorithm on UAV LiDAR dataset / Mohamad Khairan Mohd Asri by Mohd Asri, Mohamad Khairan

“…Two algorithms, the Cloth Simulation Filter (CSF) in CloudCompare and the Multiscale Curvature Classification (MCC) in Global Mapper, were tested for this purpose. …”
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Real-time Traffic Classification Algorithm Based on Hybrid of Signature Statistical and Port to Identify Internet Applications by Hamza Awad, Hamza Ibrahim, Sulaiman, Mohd Nor, Izzeldin, I. Mohd, Mohamed Saad, Mahoub, Haitham, A. Jamil

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Dynamic Bayesian Networks and Variable Length Genetic Algorithm for Dialogue Act Recognition by Ali Yahya, Anwar

“…The current dialogue act recognition models, namely cue-based models, are based on machine learning techniques, particularly statistical ones. …”
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Efficient and low complexity modulation classification algorithm for MIMO systems by Bahloul, M.R., Yusoff, M.Z., Saad, M.N.M.

“…The classification performance of the proposed algorithm was evaluated via extensive simulations under different operating conditions and was also compared with the one obtained with the optimal Hybrid Likelihood Ratio Test (HLRT) approach. …”
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High voltage transmission line fault classification based on neural network trained by particle swarm optimization by Zukri, Muhamad Amirul Aizad

“…This research has shown that the resulted in the excellent classification performances is extremely accurate and error of performance is decrease when apply the PSO algorithm. …”
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Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms by Teoh, Chin Chuang

“…The advantage of the cluster labelling algorithm compared to co-spectral plot and maximum-likelihood classifier was the algorithm provided a rapid production of high accuracy classification map.…”
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