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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
A direct ensemble classifier for imbalanced multiclass learning
Published 2012“…Researchers have shown that although traditional direct classifier algorithm can be easily applied to multiclass classification, the performance of a single classifier is decreased with the existence of imbalance data in multiclass classification tasks.Thus, ensemble of classifiers has emerged as one of the hot topics in multiclass classification tasks for imbalance problem for data mining and machine learning domain.Ensemble learning is an effective technique that has increasingly been adopted to combine multiple learning algorithms to improve overall prediction accuraciesand may outperform any single sophisticated classifiers.In this paper, an ensemble learner called a Direct Ensemble Classifier for Imbalanced Multiclass Learning (DECIML) that combines simple nearest neighbour and Naive Bayes algorithms is proposed. …”
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3
Frequent Lexicographic Algorithm for Mining Association Rules
Published 2005“…The Flex algorithm and the other two existing algorithms Apriori and DIC under the same specification are tested toward these datasets and their extraction times for mining frequent patterns were recorded and compared. …”
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4
Comparison Performance of Qualitative Bankruptcy Classification based on Data Mining Algorithms
Published 2018“…Knowledge discovery using data mining techniques are commonly applied in bankruptcy classification and prediction. …”
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Data mining reduction methods and performances of rules
Published 2009“…In data mining the accuracy of models are associated with the strength of the rules.However, most machine learning techniques produce a large number of rules.The consequence is with large number of rules generated,processing time is much longer. …”
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6
Setting up a new Radiology Center Technology for improvement : Data mining (Image Mining Technique)
Published 2016“…Data mining requires the use of data analysis tool containing statistical model, mathematical algorithms and machine learning methods to determine previously unknown, valid patterns and relationships in huge volume data. …”
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Monograph -
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Using predictive analytics to solve a newsvendor problem / S. Sarifah Radiah Shariff and Hady Hud
Published 2023“…Secondly, in solving every Machine Learning problem, there is no one algorithm superior to other algorithms. …”
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Book Section -
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Multiview Laplacian semisupervised feature selection by leveraging shared knowledge among multiple tasks
Published 2019“…Recently, considerable advancement has been achieved in semisupervised multitask feature selection methods, which they exploit the shared information from multiple related tasks. Besides, these algorithms have adopted manifold learning to leverage both the unlabeled and labeled data since its laborious to obtain adequate labeled training data. …”
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9
Evaluating integrated weight linear method to class imbalanced learning in video data
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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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11
Application of target detection method based on convolutional neural network in sustainable outdoor education
Published 2023“…The acquisition system of underwater camera information of manned submersibles is designed through the Single Shot-MultiBox Detector algorithm of deep learning. Furthermore, CNN is adopted to classify the underwater target images, which realizes the intelligent detection and classification of underwater targets. …”
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12
Learner’s emotion prediction using production rules classification algorithm through brain computer interface tool
Published 2018“…No EEG studies in Malaysia has been done on school children to study their emotional behaviour while learning. Classification and prediction are the functions provided by the data mining techniques that suit in EEG signal processing. …”
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13
Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…Features selection process can be considered a problem of global combinatorial optimization in machine learning. Genetic algorithm GA had been adopted to perform features selection method; however, this method could not deliver an acceptable detection rate, lower accuracy, and higher false alarm rates. …”
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Small Dataset Learning In Prediction Model Using Box-Whisker Data Transformation
Published 2020“…Hence, the aims of this study are proposing an algorithm of hybrid to generate artificial samples adopts Small Johnson Data Transformation and Box-Whisker Plot which is introduced in previous studies. …”
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16
Class binarization with self-adaptive algorithm to improve human activity recognition
Published 2018“…In order to estimate the quality of ‘pruned’ features, self-adaptive DE algorithm is proposed. Two parameters (population size and generation numbers) are adaptively adopted from number of remaining ranking features. …”
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17
A COMPARATIVE STUDY OF MACHINE LEARNING MODELS FOR PREDICTION OF AUTISM SPECTRUM DISORDER USING SCREENING DATA
Published 2023“…The project proposed using classification, which is one of the machine learning approaches to predict autism spectrum disorder. …”
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Final Year Project Report / IMRAD -
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Dynamic and adaptive execution models for data stream mining applications in mobile edge cloud computing systems / Muhammad Habib Ur Rehman
Published 2016“…The critical factors of complexity at application level include data size and data rate of continuously streaming data, the selection of data fusion and data preprocessing methods, the choice of learning models, learning rates and learning modes, and the adoption of data mining algorithms. …”
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Spatial Data Mining Model For Landfill Sites Suitability Mapping Based On Neural Networks And Multivariate Analysis
Published 2017“…The learned network was used to acquire the weights of the criteria. …”
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20
Prediction of ADHD from a small dataset using an adaptive EEG theta/beta ratio and PCA feature extraction
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Proceeding Paper
