cox regression model serves as a statistical method for analyzing the survival data, which requires some options such as hazard proportionality. in recent decades, artificial neural network model has been increasingly applied to predict survival data. this research was conducted to compare cox regression and artificial neural network models in prediction of kidney transplant survival. the prese...

As customers are the main asset of any organization, customer churn management is becoming a major task for organizations to retain their valuable customers. In the previous studies, the applicability and efficiency of hierarchical data mining techniques for churn prediction by combining two or more techniques have been proved to provide better performances than many single techniques over a nu...

Several studies have compared the prediction accuracy of different types of techniques with emphasis placed on linear and stepwise regressions, and Case-based Reasoning (CBR). We believe the use of only one type of CBR technique may bias the results, as there are others that may also be used for effort prediction. This paper has two objectives. The first is to compare the prediction accuracy of...

This study examines the capability of the Relevance Vector Machine (RVM) and Multivariate Adaptive Regression Spline (MARS) for prediction of ultimate capacity of driven piles and drilled shafts. RVM is a sparse method for training generalized linear models, while MARS technique is basically an adaptive piece-wise regression approach. In this paper, pile capacity prediction models are developed...

It is well-known that accurate prediction for network flow is very important to meet the communication requirement of internet network. This study is to propose a novel twin support vector regression algorithm for network flow forecasting. The twin support vector regression algorithm is comprised of a pair of the standard SVR. In order to show the excellent performance of twin support vector re...

this study was conducted to investigate the prediction of growth performance using linear regression and artificial neural network (ann) in broiler chicken. artificial neural networks (anns) are powerful tools for modeling systems in a wide range of applications. the ann model with a back propagation algorithm successfully learned the relationship between the inputs of metabolizable energy (kca...

In this paper we apply Conformal Prediction (CP) to the k -Nearest Neighbours Regression (k -NNR) algorithm and propose ways of extending the typical nonconformity measure used for regression so far. Unlike traditional regression methods which produce point predictions, Conformal Predictors output predictive regions that satisfy a given confidence level. The regions produced by any Conformal Pr...

The quality of software has been a main concern since the inception of computer software. To be able to produce high quality software, software developers and software testers alike need continuous improvements in their developing and testing methodologies. These improvements should result in better coverage of the input domain, efficient test cases, and in spending fewer testing resources. In ...