Search Results - (( bayesian classification model algorithm ) OR ( java implementation mining algorithm ))
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Direct approach for mining association rules from structured XML data
Published 2012“…The thesis also provides a two different implementation of the modified FLEX algorithm using a java based parsers and XQuery implementation. …”
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Thesis -
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Improved method of classification algorithms for crime prediction
Published 2014“…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
Published 2024“…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
Published 2013“…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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Study and Implementation of Data Mining in Urban Gardening
Published 2019“…Using the J48 tree algorithm implemented through WEKA API on a Java Servlet, data provided is processed to derive a health index of the plant, with the possible outcomes set to “Good,” “Okay”, or “Bad”. …”
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Computational intelligence approach for classification and risk quantification of metabolic syndrome / Habeebah Adamu Kakudi
Published 2019“…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
Published 2012“…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
Published 2018“…Keyword: Random Forest, Bayesian Inference, Classification, Regression, Missing Data.…”
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Scalable approach for mining association rules from structured XML data
Published 2009“…Many techniques have been proposed to tackle the problem of mining XML data we study the various techniques to mine XML data and yet We presented a java based implementation of FLEX algorithm for mining XML data.…”
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Mining association rules from structured XML data
Published 2009“…Many techniques have been proposed to tackle the problem of mining XML data. We study the various techniques to mine XML data and yet We presented a java based implementation of FLEX algorithm for mining XML data.…”
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A Voting Technique Of Multilayer Perceptron Ensemble For Classification Application
Published 2014“…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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A joint Bayesian optimization for the classification of fine spatial resolution remotely sensed imagery using object-based convolutional neural networks
Published 2022“…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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A Bayesian probability model for Android malware detection
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A web-based implementation of k-means algorithms
Published 2022“…This stinginess of proximity measures in data mining tools is stifling the performance of the algorithm. …”
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A Bayesian probability model for Android malware detection
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