Applying Variant Variable Regularized Logistic Regression for Modeling Software Defect Predictor

Provided by: Lecture Notes on Software Engineering (LNSE)
Topic: Software
Format: PDF
Empirical studies on software defect prediction models have come up with various predictors. In this paper, they examined variable regularized factors in conjunction with Logistic regression. Their paper was built on eight public NASA datasets commonly used in this field. They used one of the datasets for their learning classification out of which they selected the regularization factor with the best predictor model; they then used the same regularization factor to classify the other seven datasets. Their proposed algorithm Variant Variable Regularized Logistic Regression (VVRLR) and modified VVRLR

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