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Browsing Fourth Local Conference on Parallel and Soft Computing by Subject "Data mining"

Browsing Fourth Local Conference on Parallel and Soft Computing by Subject "Data mining"

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  • Decision in Planning Ceremony Using Decision Tree 
    Sin, Yi Mon Shwe; Thein, Thin Lai Lai (Fourth Local Conference on Parallel and Soft Computing, 2009-12-30)
    This paper implements the planning ceremony by using decision tree induction algorithm. Nowadays, ceremonies are held by many people in various form such as wedding, birthday, promotions, award and so on. Since there are ...
  • Developing Decision Tree Using ID3 for Paddy Classification 
    Cho, May Latt; Htun, Moe Sanda (Fourth Local Conference on Parallel and Soft Computing, 2009-12-30)
    Data Mining is the task of discovering interesting pattern from large amounts of data where the data can be stored in database, data warehouse. Data classification is the process of building a model from available data ...
  • Diagnosis of Hypothyroid Disease by Using Decision Tree Induction 
    Htut, May Zin; Win, Thin Zar (Fourth Local Conference on Parallel and Soft Computing, 2009-12-30)
    Data mining is the process of discovering useful information underlying the data. Powerful techniques are needed to extract patterns from large data because traditional statistical tools are efficient enough any more. ...
  • Divisive Hierarchical Clustering of Drugs Based on Chemical Compositions 
    Wai, Zin Mar; Win, Kalyar (Fourth Local Conference on Parallel and Soft Computing, 2009-12-30)
    Clustering is the process of grouping the data into classes or clusters. Objects within a class have high similarity in comparison to one another, but are very dissimilar to objects in other clusters. In this paper we ...
  • Implementation of Classification System for Dry Zone Plantation Based on ID3 Algorithm 
    Hlaing, Thazin (Fourth Local Conference on Parallel and Soft Computing, 2009-12-30)
    Classification is data analysis process that can be used to extract models describing important data classes or predict future data. Classification of large data sets is an important data mining problem. Decision tree, ...
  • Medical Information System for Diabetes Mellitus by using Rough Set Theory 
    Cherry, Hnin (Fourth Local Conference on Parallel and Soft Computing, 2009-12-30)
    Rough set theory is based on the establishment of equivalence classes within the given training data. All of the data samples forming an equivalence class are indiscernible, that is, the samples are identical with respect ...

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