Search Results - (( java applications mining algorithm ) OR ( knowledge solution mining algorithm ))

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

    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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    Article
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    Mining Sequential Patterns Using I-PrefixSpan by Dhany , Saputra, Rambli Dayang, R.A., Foong, Oi Mean

    Published 2007
    “…Sequential pattern mining is a relatively new data-mining problem with many areas of application. …”
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    Conference or Workshop Item
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    A web-based implementation of k-means algorithms by Lee, Quan

    Published 2022
    “…This stinginess of proximity measures in data mining tools is stifling the performance of the algorithm. …”
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    Final Year Project / Dissertation / Thesis
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    Data Classification and Its Application in Credit Card Approval by Thai , VinhTuan

    Published 2004
    “…Many intensive researches have been conducted to enhance the capability of data mining solution in providing the intelligence so that different types of businesses can make informed decisions. …”
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    Final Year Project
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    Medical diagnosis using data mining techniques / Shaiful Nizam Zamri by Shaiful Nizam , Zamri

    Published 2003
    “…Secondly, this report will review the literature part which started with basic knowledge of data mining and knowing what the basic information about data mining. …”
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    Thesis
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    An artificial immune system model as talent performance predictor / Siti ‘Aisyah Sa’dan, Hamidah Jantan and Mohd Hanapi Abdul Latif by Sa’dan, Siti ‘Aisyah, Jantan, Hamidah, Abdul Latif, Mohd Hanapi

    Published 2016
    “…Immune based algorithm is part of bio-inspired algorithms elicits theories which can act as an inspiration for computer-based solutions. …”
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    Research Reports
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    Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy by Ganesh , Krishnasamy

    Published 2019
    “…By using the proposed algorithm, the sparse coefficients are learned by exploiting the relationships among different multi-view features and leveraging the knowledge from multiple related tasks. …”
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    Thesis
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    Towards a better feature subset selection approach by Shiba, Omar A. A.

    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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    Conference or Workshop Item
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    Improving intrusion detection using genetic algorithm by Hashemi, V. Moraveji, Muda, Zaiton, Yassin, Warusia

    Published 2013
    “…The validity of this approach is verified using Knowledge Discovery and Data Mining Cup 1999 (KDD Cup ’99) dataset. …”
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    Article
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    Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

    Published 2016
    “…The simulation will be carried on WEKA tool, which allows us to call some data mining methods under JAVA environment. The proposed model will be tested and evaluated on both NSL-KDD and KDD-CUP 99 using several performance metrics.…”
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    Thesis
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    Feature and Instances Selection for Nearest Neighbor Classification via Cooperative PSO by Sharifah Sakinah, Syed Ahmad

    Published 2014
    “…Data reduction is an essential task in the data preparation phase of knowledge discovery and data mining (KDD). The reduction method contains two techniques, namely features reduction and data reduction which are commonly applied to a classification problem. …”
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    Conference or Workshop Item
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    Classification models for higher learning scholarship award decisions by Wirawati Dewi Ahmad, Azuraliza Abu Bakar

    Published 2018
    “…In this study, a data mining approach was used to propose a classification model of scholarship award result determination. …”
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    Article
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    Hybrid metaheuristics for QOS-aware service composition / Hadi Naghavipour by Hadi , Naghavipour

    Published 2022
    “…On that basis, the second contribution of this thesis is proposing a fast fuzzy evolutionary algorithm with minimal stochastic behaviour. Furthermore, this thesis contributes to the body of knowledge by introducing a novel method called Fuzzy Rough set Genetic Algorithm (FRGA) that take on efficiency of metaheuristics while reducing search space by leveraging the data mining aspect of rough set theory. …”
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    Thesis
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    A comparative study between rough and decision tree classifiers by Mohamad Mohsin, Mohamad Farhan

    Published 2008
    “…Rule-based classification system (RBC) has been widely used in many real world applications because of the easy interpretability of rules.RBC mines a collection of rule via knowledge which is hidden in dataset in order to accurately map new cases to the decision class.In the real world, the number of attribute of dataset could be very large due the capability of database technology to store much information.Following that, the large dataset may contain thousands of relationship and it will likely provide more knowledge since the interrelationship between data will give more description.Furthermore, it is also have the possibility to have most number of rules that contain unnecessary rule or redundancies in the model. …”
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    Monograph