Novel Approach of programming effort estimation by boosting and bagging approach  with feature selection using optimization.

Novel Approach of programming effort estimation by boosting and bagging approach with feature selection using optimization.
Author(s):
INDU BALA, Gagan Dhawan
Keywords:
random forest ,optimization, bagging
Abstract
In this theory highlight set is expanded by including Line of code (LOC). By utilizing these highlights exertion data is enhanced and help in programming improvement. In second part includes are chosen by utilizing Gray wolf streamlining (GWO) calculation. In the two works arbitrary woodland and examining with boosting and stowing technique is utilized which enhances the irregular backwoods preparing model. In this work Random woods with GWO and Random backwoods without GWO is contrasted and parameter Accuracy, Precision and Recall.
Article Details
Unique Paper ID: 146827 Publication Volume & Issue: Volume 5, Issue 2 Page(s): 114 - 117
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