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In this paper, we establish an effort prediction model using an artificial neural network (ANN) for complementing missing values. We add missing values to the data via collaborative filtering using the method of Tsunoda et al.'s method. In addition, we perform an evaluation experiment to compare the accuracy of the ANN model with that of the MRA model using Welch's t-test. The results show that the...
In this paper, we outline the effort prediction model and the evaluation experiment. In addition we explore the parameters in the model. The model predicts effort of embedded software developments via multiple regression analysis using the collaborative filtering. Because companies, recently, focus on methods to predict effort of projects, which prevent project failures such as exceeding deadline...
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