Search Results - (( program case mining algorithm ) OR ( java application customization algorithm ))
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Case Slicing Technique for Feature Selection
Published 2004“…Finding a good classification algorithm is an important component of many data mining projects. …”
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Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining.
Published 2005“…The accuracy for rules and classification resulted from the TIP method are compared with other methods such as Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) from Rough Set, Genetic Algorithm (GA), Johnson reducer, HoltelR method, Multiple Regression (MR), Neural Network (NN), Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5); all other classifiers that are mostly used in the classification tasks. …”
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An efficient and effective case classification method based on slicing
Published 2006“…The paper also discusses two of common classification algorithms that are used either in data mining or in general AI. …”
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Facilitating resource allocation decision through Bibliomining: the case of UTM's library / Md Razib Karno
Published 2015“…With nearly 1 million records of collection in various formats, the Library of Universiti Teknologi Malaysia has been chosen as the case study for the research. The data mining technique was adopted to explore the relationship among statistically patterned and clustered bibliographic data. …”
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Towards a better feature subset selection approach
Published 2010“…The selection of the optimal features subset and the classification has become an important issue in the data mining field.We propose a feature selection scheme based on slicing technique which was originally proposed for programming languages.The proposed approach called Case Slicing Technique (CST).Slicing means that we are interested in automatically obtaining that portion 'features' of the case responsible for specific parts of the solution of the case at hand.We show that our goal should be to eliminate the number of features by removing irrelevant once.Choosing a subset of the features may increase accuracy and reduce complexity of the acquired knowledge.Our experimental results indicate that the performance of CST as a method of feature subset selection is better than the performance of the other approaches which are RELIEF with Base Learning Algorithm (C4.5), RELIEF with K-Nearest Neighbour (K-NN), RELIEF with Induction of Decision Tree Algorithm (ID3) and RELIEF with Naïve Bayes (NB), which are mostly used in the feature selection task.…”
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Predicting Student Performance in Object Oriented Programming Using Decision Tree : A Case at Kolej Poly-Tech Mara, Kuantan
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Propositional satisfiability method in rough classification modeling for data mining
Published 2002“…Two models, Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) to represent the minimal reduct computation problem were proposed. …”
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Enhancing obfuscation technique for protecting source code against software reverse engineering
Published 2019“…The proposed technique can be enhanced in the future to protect games applications and mobile applications that are developed by java; it can improve the software development industry. …”
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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“…At application level, the program components need to handle continuously streaming data in order to perform knowledge discovery operations. …”
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Design & Development of a Robotic System Using LEGO Mindstorm
Published 2006“…Since the model is built using LEGO bricks, the model is fully customized, in term of its applications, to perform any relevant tasks. …”
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Dynamic investment model for the restructed power market in the presence of wind source
Published 2014“…In the third step, the long term optimal investment strategies of the hybrid wind-thermal investor are determined based on the dynamic programming algorithm by considering the long term states of demand growth and fuel price uncertainties. …”
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Thesis -
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