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Using Bayesian regression and EM algorithm with missing handling for software effort prediction

https://doi.org/10.1016/j.infsof.2014.10.005

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What this work says

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AREION: Software effort estimation based on multiple regressions with adaptive recursive data partitioning

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A new imputation method for small software project data sets

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Can k-NN imputation improve the performance of C4.5 with small software project data sets? A comparative evaluation

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Software effort models should be assessed via leave-one-out validation

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Text Classification from Labeled and Unlabeled Documents using EM

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LII. An essay towards solving a problem in the doctrine of chances. By the late Rev. Mr. Bayes, F. R. S. communicated by Mr. Price, in a letter to John Canton, A. M. F. R. S

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Machine learning approaches to estimating software development effort

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Estimating software project effort using analogies

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Software cost estimation with incomplete data

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Analyzing data sets with missing data: an empirical evaluation of imputation methods and likelihood-based methods

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A Systematic Review of Software Development Cost Estimation Studies

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A systematic review of software development cost estimation studies

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Data Mining Techniques for Software Effort Estimation: A Comparative Study

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Active learning and effort estimation: Finding the essential content of software effort estimation data

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Maximum Likelihood from Incomplete Data Via the EM Algorithm

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Pattern classification

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Statistical Analysis With Missing Data

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Statistical Analysis with Missing Data.

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The state‐of‐the‐art in software development effort estimation

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