Search Results - (( bayesian classification modeling algorithm ) OR ( evolution optimization learning algorithm ))

Improved method of classification algorithms for crime prediction by Babakura, Abba, Sulaiman, Md. Nasir, Yusuf, Mahmud Ahmad

“…This paper compares two different classification algorithms namely - Naïve Bayesian and Back Propagation (BP) for predicting 'Crime Category' for distinctive states in USA. …”
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Predicting building damage grade by earthquake: a Bayesian Optimization-based comparative study of machine learning algorithms by Al-Rawashdeh, Mohammad, Al Nawaiseh, Moh’d, Yousef, Isam, Bisharah, Majdi, Alkhadrawi, Sajeda, Al-Bdour, Hamza

“…Research should address class imbalance, because it affects model performance. Bayesian Optimization helps models acquire data patterns, improving classification accuracy. …”
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Feature extraction using active appearance model algorithm with Bayesian classification approach by Nuruzzaman, Mohammad, Hussain, Azham, Mohamad Tahir, Hatim, Abu Seman, Mohamad Amir

“…This study enhances invariant recognition of human faces and analysis to improve face verification and identification performance using Active Appearance Model (AAM) for feature extraction with Bayesian classification approach. …”
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Comparison between Lamarckian Evolution and Baldwin Evolution of neural network by Taha, Imad, Inazy, Qabas

“…Hybrid genetic algorithms are the combination of learning algorithms(Back propagation), usually working as evaluation functions, and genetic algorithms. …”
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Classification of heart disease with machine learning: a comparison of grid search, random search, and Bayesian Optimization by Andi, Tri, Ismail, Amelia Ritahani, Pranolo, Andri, Kusuma, Candra Juni Cahyo

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Differential evolution for neural networks learning enhancement by Ismail Wdaa, Abdul Sttar

“…To overcome this problem, Differential Evolution (DE) has been used to determine optimal value for ANN parameters such as learning rate and momentum rate and also for weight optimization. …”
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Computational intelligence approach for classification and risk quantification of metabolic syndrome / Habeebah Adamu Kakudi by Habeebah Adamu , Kakudi

“…Genetic Algorithm(GA) is used to optimize the order of sequence of the input sample and the parameters of the Bayesian ARTMAP (BAM). …”
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Comparative Analysis Using Bayesian Approach To Neural Network Of Translational Initiation Sites In Alternative Polymorphic Contex by Herman, Nanna Suryana, Husin, Nurul Arneida, Hussin, Burairah

“…The objectives of this paper are to develop useful algorithms and to build a new classification model for the case study.The first approach of neural network includes training on algorithms of Resilient Backpropagation,Scaled Conjugate Gradient Backpropagation and Levenberg-Marquardt.The outputs are used in comparison with Bayesian Neural Network for efficiency comparison.The results showed that Resilient Backpropagation have the consistency in all measurement but performs less in accuracy.In second approach,the Bayesian Classifier_01 outperforms the Resilient Backpropagation by successfully increasing the overall prediction accuracy by 16.0%.The Bayesian Classifier_02 is built to improve the accuracy by adding new features of chemical properties as selected by the Information Gain Ratio method,and increasing the length of the window sequence to 201.The result shows that the built model successfully increases the accuracy by 96.0%.In comparison,the Bayesian model outperforms Tikole and Sankararamakrishnan (2008) by increasing the sensitivity by 10% and specificity by 26%. …”
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Bayesian random forests for high-dimensional classification and regression with complete and incomplete microarray data by Oyebayo, Olaniran Ridwan

“…Keyword: Random Forest, Bayesian Inference, Classification, Regression, Missing Data.…”
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A Voting Technique Of Multilayer Perceptron Ensemble For Classification Application by Talib, Hafizah

“…MLPE is produced from singular MLPs that are diverse in term of training algorithm and their initial weights. Three training algorithms used are Levenberg-Marquardt (LM), Resilient Backpropagation (RP) and Bayesian Regularization (BR). …”
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Developing a hybrid model for accurate short-term water demand prediction under extreme weather conditions: a case study in Melbourne, Australia by Zubaidi S.L., Kumar P., Al-Bugharbee H., Ahmed A.N., Ridha H.M., Mo K.H., El-Shafie A.

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A joint Bayesian optimization for the classification of fine spatial resolution remotely sensed imagery using object-based convolutional neural networks by Azeez, Omer Saud, M. Shafri, Helmi Z., Alias, Aidi Hizami, Haron, Nuzul Azam

“…The analysis of CNN variants within the proposed classification workflow showed that the HybridSN model achieved the best results compared to 2D and 3D CNNs. …”
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Broadening selection competitive constraint handling algorithm for faster convergence by Shaikh, T.A., Hussain, S.S., Tanweer, M.R., Hashmani, M.A.

“…In this study, the BSCCH algorithm has been coupled with Differential Evolution algorithm as a proof of concept because it is found to be an efficient algorithm in the literature for constrained optimization problems. …”
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A Bayesian probability model for Android malware detection by Sharfah Ratibah, Tuan Mat, Mohd Faizal, Ab Razak, Mohd Nizam, Mohmad Kahar, Juliza, Mohamad Arif

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Sentiment analysis regarding marital issues using Naive Bayes algorithm / Farah Nabila Mohd Razali by Mohd Razali, Farah Nabila

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A Bayesian probability model for Android malware detection by Sharfah Ratibah, Tuan Mat, Mohd Faizal, Ab Razak, Mohd Nizam, Mohmad Kahar, Juliza, Mohamad Arif, Ahmad Firdaus, Zainal Abidin

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A Bayesian Approach to Explore Risk Factors for Respiratory Dysfunction in Intensive Care Unit Patient by Shah N.B.N.H., Razak N.N.B.A., Samah A.B.A., Razak N.A.B.A., Ramasamy A., Suhaimi F.M., Chase J.G.

Towards personalized intensive care decision support using a Bayesian network: A multicenter glycemic control study by Abu-Samah A., Razak N.N.A., Suhaimi F.M., Jamaludin U.K., Chase J.G.

Dual optimization approach in discrete Hopfield neural network by Guo, Yueling, Zamri, Nur Ezlin, Mohd Kasihmuddin, Mohd Shareduwan, Alway, Alyaa, Mansor, Mohd. Asyraf, Li, Jia, Zhang, Qianhong

“…Therefore, this research contributes to the improvement of the learning and retrieval phases by integrating the Hybrid Differential Evolution Algorithm and Swarm Mutation respectively. …”
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Predicting the classification of heart failure patients using optimized machine learning algorithms by Ahmed, Marzia, Mohd Herwan, Sulaiman, Hassan, Md Maruf, Bhuiyan, Touhid

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