Titlebook: Soft Computing in Data Science; First International Michael W. Berry,Azlinah Mohamed,Bee Wah Yap Conference proceedings 2015 Springer Scie

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Data Projection Effects in Frequent Itemsets MiningM that affects the overall performance. The aim is to speed up the searching process by rearranging the items in a more compact form and to fit all the items in the data set in main memory efficiently without losing any information. The data refer to how the data set is stored in the main memory bef

陈腐思想

Data Quality Issues in Data Migrationived, integrated, maintained, processed and loaded. The data migration project requires the data to be extracted from multiple sources before being cleansed and transformed. Once the data are cleansed and transformed, the data will be loaded into a new system. Therefore, data cleansing is the most i

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Comparisons of ADABOOST, KNN, SVM and Logistic Regression in Classification of Imbalanced Datasete imbalanced data issue has led to an influx of methods, either resolving the imbalance issue at data or algorithmic level. The R programming language is one of the many tools available for data mining. This paper compares some classification algorithms in R for an imbalanced medical data set. The c

CAMP

Finding Significant Factors on World Ranking of e-Governments by Feature Selection Methods over KPIs paper, a case of e-Government ranking is studied by attempting to find the significance of each KPIs which leads to resultant rank of a country. Significant factors in this context are inferred as some degrees of relations between the input variables (which are the KPIs in this case) and the final

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Possibility Vague Soft Expert Set Theory and Its Application in Decision Makingets to possibility vague soft sets. The complement, union, intersection, AND and OR operations as well as some related concepts pertaining to this notion are defined. The algebraic properties such as the De Morgan’s laws and the relevant laws of possibility vague soft expert sets are studied and sub