Search Results - (("based learning algorithm") OR ((("pattern search algorithm") OR ("pattern using algorithm"))))

Evaluating the effects of the dual tree complex wavelet transform and the adaptive rood pattern search algorithm on a video codec by V.V., Yap, U.Y., Oktiawati

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A harmony search-based learning algorithm for epileptic seizure prediction by Kee, Huong Lai, Zainuddin, Zarita, Ong, Pauline

“…The proposed harmony search-based learning algorithm is used in the task of epileptic seizure prediction. …”
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A modified generalized RBF model with EM-based learning algorithm for medical applications by Ma, Li Ya, Abdul Rahman, Abdul Wahab, Quek, Chai

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Fractional Stochastic Gradient Descent Based Learning Algorithm For Multi-layer Perceptron Neural Networks by Sadiq, A., Yahya, N.

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Optimizing the SEIRD model for COVID-19 in Malaysia using pymoo framework by Abdul Hadi, Muhammad Salihi, Amran, Muhammad Aiman Haziqh, Zulkarnain, Norsyahidah

“…To solve this, the Nelder-Mead and Pattern Search algorithms were recommended. While Nelder-Mead is widely available in Python optimization libraries, Pattern Search is less common, which motivated the choice of the Pymoo multi-objective optimization framework for this study. …”
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The effect of job satisfaction on the relationship between organizational culture and organizational performance by Imran, Muhammad

“…Furthermore, it is hybridized with the Pattern Search algorithm to ensure the optimality of the solution. …”
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Improved flower pollination optimization algorithm based on swap operator and dynamic switch probability selection by Iqbal, Muhammad

“…Furthermore, it is hybridized with the Pattern Search algorithm to ensure the optimality of the solution. …”
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Hybrid of firefly algorithm and pattern search for solving optimization problems by Wahid, Fazli, Ghazali, Rozaida

“…In the final stage, the optimized values obtained from the FA during its maximum number of iteration are given as inputs to the pattern search algorithm. The pattern search is an optimization algorithm that further optimizes the values obtained in the maximum iterations of standard FA. …”
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Case Slicing Technique for Feature Selection by A. Shiba, Omar A.

“…CST was compared to other selected classification methods based on feature subset selection such as Induction of Decision Tree Algorithm (ID3), Base Learning Algorithm K-Nearest Nighbour Algorithm (k-NN) and NaYve Bay~sA lgorithm (NB). …”
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Towards a better feature subset selection approach by Shiba, Omar A. A.

“…The selection of the optimal features subset and the classification has become an important issue in the data mining field.We propose a feature selection scheme based on slicing technique which was originally proposed for programming languages.The proposed approach called Case Slicing Technique (CST).Slicing means that we are interested in automatically obtaining that portion 'features' of the case responsible for specific parts of the solution of the case at hand.We show that our goal should be to eliminate the number of features by removing irrelevant once.Choosing a subset of the features may increase accuracy and reduce complexity of the acquired knowledge.Our experimental results indicate that the performance of CST as a method of feature subset selection is better than the performance of the other approaches which are RELIEF with Base Learning Algorithm (C4.5), RELIEF with K-Nearest Neighbour (K-NN), RELIEF with Induction of Decision Tree Algorithm (ID3) and RELIEF with Naïve Bayes (NB), which are mostly used in the feature selection task.…”
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An experimental evaluation of case slicing as a new classification technique by Shiba, Omar A. A., Sulaiman, Md. Nasir, Ahmad, Fatimah, Mamat, Ali

“…Lastly, it compares the proposed approach with other selected approaches such as the K-Nearest Neighbour (K-NN), Base Learning Algorithm (C4.5) and Naïve Bayes classifier (NB) in solving the classification problems. …”
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An efficient and effective case classification method based on slicing by Shiba, Omar A. A., Sulaiman, Md. Nasir, Mamat, Ali, Ahmad, Fatimah

“…The algorithms are: Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5). The paper also studies the comparison between the proposed method and the two selected classification algorithms using several domains.…”
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A new text-based w-distance metric to find the perfect match between words by Ali, M., Jung, L.T., Hosam, O., Wagan, A.A., Shah, R.A., Khayyat, M.

“…The k-NN algorithm is an instance-based learning algorithm which is widely used in the data mining applications. …”
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A modified weighted support vector machine (WSVM) to reduce noise data in classification problem by Mohd Dzulkifli, Syarizul Amri

“…To overcome SVM drawback for noise data problem, WSVM using KPCM algorithm was used but WSVM using kernel-based learning algorithm such as KPCM algorithm suffer from training complexity, expensive computation time and storage memory when noise data contaminate training data. …”
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A modified weighted support vector machine (WSVM) to reduce noise data in classification problem by Mohd Dzulkifli, Syarizul Amri

“…To overcome SVM drawback for noise data problem, WSVM using KPCM algorithm was used but WSVM using kernel-based learning algorithm such as KPCM algorithm suffer from training complexity, expensive computation time and storage memory when noise data contaminate training data. …”
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Advances of metaheuristic algorithms in training neural networks for industrial applications by Chong H.Y., Yap H.J., Tan S.C., Yap K.S., Wong S.Y.

Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining. by Saeed, Walid

“…The accuracy for rules and classification resulted from the TIP method are compared with other methods such as Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) from Rough Set, Genetic Algorithm (GA), Johnson reducer, HoltelR method, Multiple Regression (MR), Neural Network (NN), Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5); all other classifiers that are mostly used in the classification tasks. …”
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