Paper Title
Classifiers Based On Error Measures
Abstract
Software project can be completely predicting the most realistic effort using Software Cost Estimation.
There are variety of methods and models trying to improve the estimation procedure of software project
development and application. From the variety of methods developed the need for comparisons to determine the best
model. Here, we propose some prediction models and error measures over datasets identifying those which have significant
differences in accuracy. The proposed context is applied in a large scale structure of comparing prediction models over
datasets.
Keywords— Softwarecost Estimation, Management, Metrics/Measurement, Prediction Method.