exampleresult


Modified Iris-data preprocessed with 540 combinations and evaluated with 
support vector machine classifier. 


datasets

Preprocessing is often the most time-consuming phase in data analysis
and preprocessing transformations interdependent in unexpected
ways. This package helps to make preprocessing faster and more effective. It
provides an S4 framework for creating and evaluating preprocessing combinations
for classification, clustering and outlier detection. The framework supports
adding of user-defined preprocessors and preprocessing phases. Default preprocessors
can be used for low variance removal, missing value imputation, scaling, outlier
removal, noise smoothing, feature selection and class imbalance correction.

exampleresult: preprocomb example

Description

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