Search Results - (( java application optimisation algorithm ) OR ( basic evaluation bayes algorithm ))
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1
Study and Implementation of Data Mining in Urban Gardening
Published 2019“…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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2
An ensemble feature selection method to detect web spam
Published 2018“…Content features of standard dataset of WEBSPAM-UK2007 are used for evaluation. Bayes network classifier is used along with 70-30% training-testing spilt of dataset. …”
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3
A study on personalized recommender system using social media
Published 2020“…These machine learning algorithm processes the data set obtained. The evaluation on these algorithm is done to evaluate accuracy of the algorithm. …”
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Final Year Project / Dissertation / Thesis -
4
Mining The Basic Reproduction Number (R0) Forecast For The Covid Outbreak
Published 2022“…All the classification accuracies obtained were above the baseline accuracy. The COVID-19 Basic Reproduction Number, R0 a predictive model is developed using a linear regression classification algorithm to predict the COVID-19 Basic Reproduction Number, Robased on the actual COVID-19 Basic Reproduction Number, R0. …”
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Monograph -
5
Web-based expert system for material selection of natural fiber- reinforced polymer composites
Published 2015“…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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Thesis -
6
A Machine Learning Classification Approach to Detect TLS-based Malware using Entropy-based Flow Set Features
Published 2022“…Furthermore, using the basic features, TLSMalDetect achieved the highest accuracy of 93.69% by Naïve Bayes (NB) among the ML algorithms applied. …”
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7
Deep learning-based breast cancer detection and classification using histopathology images / Ghulam Murtaza
Published 2021“…The extracted features are evaluated through six machine learning (ML) classifiers namely softmax, k-nearest neighbor (kNN), support vector machine, linear discriminant analysis, decision tree, and naive Bayes. …”
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Thesis
