Dotnet IEEE Final Year Projects 2012 Horizontal Aggregations in SQL to Prepare Data Sets for Data Mining Analysis

Dotnet IEEE Final Year Projects 2012 Horizontal Aggregations in SQL to Prepare Data Sets for Data Mining Analysis

Horizontal Aggregations in SQL to Prepare Data Sets for Data Mining Analysis

Abstract:

Preparing a data set for analysis is generally the most time consuming task in a data mining project, requiring many complex SQL queries, joining tables and aggregating columns. We propose simple, yet powerful, methods to generate SQL code to return aggregated columns in a horizontal tabular layout, returning a set of numbers instead of one number per row. This new class of functions is called horizontal aggregations. Horizontal aggregations build data sets with a horizontal denormalized layout (e.g. point-dimension, observation-variable, instance-feature).

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