Search Results - (( problem using bayesian algorithm ) OR ( java application mining algorithm ))
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Direct approach for mining association rules from structured XML data
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Classification System for Heart Disease Using Bayesian Classifier
Published 2007“…In this system a Bayesian algorithm was used in order to implement the system. …”
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4
Dynamic Bayesian networks and variable length genetic algorithm for designing cue-based model for dialogue act recognition
Published 2010“…The model is, essentially, a dynamic Bayesian network induced from manually annotated dialogue corpus via dynamic Bayesian machine learning algorithms. …”
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A Comparison Between Levenberg-Marquardt (LM) Intelligent System And Bayesian Regularization (BR) Intelligent System For Flow Regime Classification
Published 2006“…ECT measured the different capacitance value of fluid and produced the data for the classification problem. Multilayed Perceptron (MLP), a type of artificial neural network (ANN) which is widely used in a classification problem is developed using MATLAB 7®. …”
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Fuzzy modeling of brain tissues in Bayesian segmentation of brain MR images
Published 2010“…A two-fold fuzzy segmentation algorithm based on Bayesian method is proposed in this paper. …”
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Dynamic Bayesian Networks and Variable Length Genetic Algorithm for Dialogue Act Recognition
Published 2007“…The results are compared with the results of static Bayesian networks and naïve bayes. The results confirm the merits of using dynamic Bayesian networks for dialogue act recognition. …”
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8
Statistical approach on grading: mixture modeling
Published 2006“…A solution to this problem is using the Markov Chain Monte Carlo method namely Gibbs sampler algorithm. …”
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Study and Implementation of Data Mining in Urban Gardening
Published 2019“…Attached sensors generate data and send these data to the Java Servlet application through a WIFI module. These data are processed and stored in appropriate formats in a MySQL server database. …”
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Efficient Bayesian spatial prediction with mobile sensor networks using Gaussian Markov random fields
Published 2013“…In this paper, we consider the problem of predicting a large scale spatial field using successive noisy measurements obtained by mobile sensing agents. …”
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Efficient Bayesian spatial prediction with mobile sensor networks using Gaussian Markov random fields
Published 2013“…In this paper, we consider the problem of predicting a large scale spatial field using successive noisy measurements obtained by mobile sensing agents. …”
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Efficient Bayesian spatial prediction with mobile sensor networks using Gaussian Markov random fields
Published 2013“…In this paper, we consider the problem of predicting a large scale spatial field using successive noisy measurements obtained by mobile sensing agents. …”
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13
Efficient Bayesian spatial prediction with mobile sensor networks using Gaussian Markov random fields
Published 2013“…In this paper, we consider the problem of predicting a large scale spatial field using successive noisy measurements obtained by mobile sensing agents. …”
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Efficient Bayesian spatial prediction with mobile sensor networks using Gaussian Markov random fields
Published 2013“…In this paper, we consider the problem of predicting a large scale spatial field using successive noisy measurements obtained by mobile sensing agents. …”
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Extreme air pollutant data analysis using classical and Bayesian approaches
Published 2015“…The univariate and bivariate extreme processes have been considered extensively using a frequentist perspective and recently there has been an increasing interest in the application of Bayesian methods to EV problems. …”
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The use of the Bayesian approach in the formation of the student's competence in the ICT direction
Published 2019“…To effectively use the Bayesian approach, a high-quality software product is needed that implements the mathematical ideas of Bayesian networks in practice. …”
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Predicting building damage grade by earthquake: a Bayesian Optimization-based comparative study of machine learning algorithms
Published 2024“…Using metrics, this study evaluates Random Forest, ElasticNet, and Decision Tree algorithms. …”
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Color Image Segmentation Based on Bayesian Theorem for Mobile Robot Navigation
Published 2009“…A useful property of the statistical classifier like Bayesian is that, it is optimal in the sense that it minimizes the expected mis classification rate. …”
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19
Mining Sequential Patterns Using I-PrefixSpan
Published 2007“…Sequential pattern mining is a relatively new data-mining problem with many areas of application. …”
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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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