Multivariate linear regression models have been commonly used as software efort prediction models. To improve the prediction accuracy, it is a common practice to transform (especially, log-transform) the data before building a model, although its theoretical basis is not necessarily clear. This paper reveals that the log-transformed linear regression model (log-log regression model) is equal to the exponential model, which is suitable to characterize various relationships among software related metrics. However, when using a log-log regression model, the result of inverse transformation tends to under-estimate the efort. This paper also introduces a method to correct such bias.
|Number of pages||6|
|Publication status||Published - Dec 1 2010|
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