Search Results - (( knowledge evaluation mining algorithm ) OR ( java application 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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    An Improved C4.5 Data Mining Driven Algorithm for the Diagnosis of Coronary Artery Disease by Haruna, A.A., Muhammad, L.J., Yahaya, B.Z., Garba, E.J., Oye, N.D., Jung, L.T.

    Published 2019
    “…This research used an im-proved C4.5 data mining algorithm for the diagnosis of CAD. A performance evaluation of the improved algorithm was carried out against the traditional C4.5 Algorithm. …”
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    Conference or Workshop Item
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    An efficient algorithm to discover large and frequent itemset in high dimensional data by Zulkurnain, Nurul Fariza

    Published 2019
    “…For this reason, this research has proposed two new algorithms; RARE and RARE II, which mine colossal closed itemsets. …”
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    Monograph
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    Evaluations of oil palm fresh fruit bunches maturity degree using multiband spectrometer by Tuerxun, Adilijiang

    Published 2017
    “…Furthermore, the Lazy-IBK algorithm have been validated to produce the best classifier model, with the machine learning algorithm performance of 65.26%, recall of 65.3%, and 65.4% F-measured as compared to other evaluated machine learning classifier algorithms proposed within the WEKA data mining algorithm. …”
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    Thesis
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    Improved BVBUC algorithm to discover closed itemsets in long biological datasets by Md Zaki, Fatimah Audah, Zulkurnain, Nurul Fariza

    Published 2019
    “…The task in mining closed frequent itemsets requires the algorithm to mine the frequent ones then determine its closure. …”
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    Article
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    Dissimilarity algorithm on conceptual graphs to mine text outliers by Kamaruddin, Siti Sakira, Hamdan, Abdul Razak, Abu Bakar, Azuraliza, Mat Nor, Fauzias

    Published 2009
    “…The graphical text representation method such as Conceptual Graphs (CGs) attempts to capture the structure and semantics of documents.As such, they are the preferred text representation approach for a wide range of problems namely in natural language processing, information retrieval and text mining.In a number of these applications, it is necessary to measure the dissimilarity (or similarity) between knowledge represented in the CGs.In this paper, we would like to present a dissimilarity algorithm to detect outliers from a collection of text represented with Conceptual Graph Interchange Format (CGIF).In order to avoid the NP-complete problem of graph matching algorithm, we introduce the use of a standard CG in the dissimilarity computation.We evaluate our method in the context of analyzing real world financial statements for identifying outlying performance indicators.For evaluation purposes, we compare the proposed dissimilarity function with a dice-coefficient similarity function used in a related previous work.Experimental results indicate that our method outperforms the existing method and correlates better to human judgements. …”
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    Conference or Workshop Item
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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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    DATA CLASSIFICATION SYSTEM WITH FUZZY NEURAL BASED APPROACH by LUONG, TRUNG TUAN

    Published 2005
    “…The project's objective is identifying the available data mining algorithms in data classification and applying new data mining algorithm to perform classification tasks. …”
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    Final Year Project
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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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    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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    Discovering decision algorithm from a distance relay event report by Othman, Mohammad Lutfi, Aris, Ishak, Abdullah, Senan Mahmood, Ali, Md. Liakot, Othman, Mohammad Ridzal

    Published 2009
    “…In this study rough-set-based data mining strategy was formulated to discover distance relay decision algorithm from its resident event report. …”
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    Article
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    Evaluation and optimization of frequent, closed and maximal association rule based classification by Mohd Shaharanee, Izwan Nizal, Hadzic, Fedja

    Published 2014
    “…Real world applications of association rule mining have well-known problems of discovering a large number of rules, many of which are not interesting or useful for the application at hand.The algorithms for closed and maximal item sets mining significantly reduce the volume of rules discovered and complexity associated with the task, but the implications of their use and important differences with respect to the generalization power, precision and recall when used in the classification problem have not been examined.In this paper, we present a systematic evaluation of the association rules discovered from frequent, closed and maximal item set mining algorithms, combining common data mining and statistical interestingness measures, and outline an appropriate sequence of usage.The experiments are performed using a number of real-world datasets that represent diverse characteristics of data/items, and detailed evaluation of rule sets is provided as a whole and w.r.t individual classes. …”
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    Article
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    Investigation of Data Mining Using Pruned Artificial Neural Network Tree by Kalaiarasi, S. M. A., Sainarayanan, Gopala, Ali Chekima, Jason Teo

    Published 2008
    “…A major drawback associated with the use of artificial neural networks for data mining is their lack of explanation capability. While they can achieve a high predictive accuracy rate, the knowledge captured is not transparent and cannot be verified by domain experts. …”
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    Article