Search Results - (( variable using sparse algorithm ) OR ( java application optimisation algorithm ))

Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

“…The system is essentially a three-part development, utilising Android, Java Servlets, and Arduino platforms to create an optimised and automated urban-gardening system. …”
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Counting roots of the Polynomial systems by using mixed volume of the Newton polytopes / Nur Suhailah Norazhar, Nur Ain Sofiya Zainuri and Nor Suhada Mohd Rosdi by Norazhar, Nur Suhailah, Zainuri, Nur Ain Sofiya, Mohd Rosdi, Nor Suhada

“…These sparse matrices are then used to generate the determinant by using Maple 2015. …”
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Minimum regularized covariance determinant and principal component analysis-based method for the identification of high leverage points in high dimensional sparse data by Siti Zahariah, Midi, Habshah

“…The main aim of this paper is to propose a novel method (RMD-MRCD-PCA) of identification of High Leverage Points (HLPs) in high-dimensional sparse data. It is to address the weakness of the Robust Mahalanobis Distance (RMD) method which is based on the Minimum Regularized Covariance Determinant (RMD-MRCD), which indicates a decrease in its performance as the number of independent variables (p) increases. …”
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Robust diagnostics and variable selection procedure based on modified reweighted fast consistent and high breakdown estimator for high dimensional data by Baba, Ishaq Abdullahi

“…Sure screening-based correlation methods are popular tools used to select the most significant variables in the true model in sparse and high dimensional analysis. …”
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Web-based expert system for material selection of natural fiber- reinforced polymer composites by Ahmed Ali, Basheer Ahmed

“…Finally, the developed expert system was deployed over the internet with central interactive interface from the server as a web-based application. As Java is platform independent and easy to be deployed in web based application and accessible through the World Wide Web (www), this expert system can be one stop application for materials selection.…”
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Robust correlation feature selection based support vector machine approach for high dimensional datasets by Baba, Ishaq Abdullahi, Mohammed, Mohammed Bappah, Jillahi, Kamal Bakari, Umar, Aliyu, Hendi, Hasan Talib

“…Correlation-based feature selection methods are popular tools used to select the most important variables to include the true model in the analysis of sparse and high-dimensional models. …”
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Support vector machine and its applications for linear and nonlinear regression in the presence of outliers of high dimensional data by Sleabi, Waleed Dhhan

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Sediment model for natural and man-made channels using general regression neural network by Junaidah, Ariffin, Nurashikin, Ahmad Kamal, Muhamad Syahreen, Sa’adon, Mohd Nasir, Taib, Suhaimi, Abdul-Talib, Aminuddin, Abd-Ghani, Nor Azazi, Zakaria, Ahmad Shukri, Yahaya

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Bayesian random forests for high-dimensional classification and regression with complete and incomplete microarray data by Oyebayo, Olaniran Ridwan

“…Random Forests (RF) are ensemble of trees methods widely used for data prediction, interpretation and variable selection purposes. …”
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