1 / 14

Software Prediction Models

Software Prediction Models. Forecasting the costs of software development. Prediction Study Outcomes Vary. Estimation-by-analogy beats regression Or not Classification and regression trees (CART) beats regression Or not Artificial neural networks beat regression Or not.

alamea
Download Presentation

Software Prediction Models

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Software Prediction Models Forecasting the costs of software development

  2. Prediction Study Outcomes Vary • Estimation-by-analogy beats regression • Or not • Classification and regression trees (CART) beats regression • Or not • Artificial neural networks beat regression • Or not

  3. Why Are The Results Conflicting? • Poor data or research procedure • Complex techniques may require expert users; hence applications may vary • Small sample size • Measurement process that is flawed • Selective use of differing parameters may result in different rankings

  4. Key Terms • Accuracy indicator • Some measure of a process • A summary statistic based on that measure • Leave-one-out cross-validation • Arbitrary function approximator taxonomy • Many-data versus sparse-data • Linear versus nonlinear • Supervised versus unsupervised • Reliability versus validity

  5. Indicator 1: MMRE • Mean magnitude of relative error (MMRE) is an average where the MRE=|actual-prediction|/actual • Claimed advantages of MMRE • Compare across data sets* • Independent of units • Compare across differing prediction models* • Scale independence *An hypothesis challenged by this paper

  6. Indicator 2: MER • Magnitude of the error relative to the estimate (MER) is defined asMER = |actual-prediction|/prediction

  7. Indicator 3: AR • The absolute residual (AR) is defined asAR = |actual-prediction|

  8. Other Measures • Standard deviation (SD) • Relative standard deviation (RSD) • Log standard deviation (LSD) • Balanced relative error (BRE) • Inverted balanced relative error (IBRE)

  9. Standard Deviation of Residuals, Denoted SD

  10. Algebraic Simplification

  11. Relative Standard Deviation (RSD)

  12. Log Standard Deviation (LSD)

  13. Balanced Relative Error (BRE)

  14. Inverted Balanced Relative Error (IBRE)

More Related