In recent years, neural networks are widely being used in areas where conventional statistical methods were used. This paper compares regression and neural networks on a real life data and two simulated examples. The results show that regression is much better than neural networks for skewed data. General guidelines are suggested to improve the performance of neural networks for skewed data. (C) 200
International audienceNeural networks are used increasingly as statistical models. The performance o...
This dissertation is designed to answer the following questions: (1) Which measurement model is bett...
Many real-life dependencies can be reasonably accurately described by linear functions. If we want a...
The aim of this research was to compare the data analytic applicability of a backpropagated neural n...
Neural networks are being used in areas of prediction and classification, the areas where statistica...
The purpose of this paper is to compare and contrast traditional regression models with a neural net...
In this paper, Artificial Neural Networks (ANN) and Regression Analysis models were considered to de...
This research work presents new development in the field of natural science, where comparison is mad...
Introduction: Artificial neural networks mimic brains behavior. They are able to predict and feature...
The current study provides an exposition of artificial neural network (ANN) methodology in the conte...
In this paper, Artificial Neural Networks (ANN) and Regression Analysis models were considered to de...
The purpose of this paper is to compare and contrast traditional regression models with a neural net...
The current study provides an exposition of artificial neural network (ANN) methodology in the conte...
This paper gives a brief overview of artificial neural networks which may be used to model data simi...
Many real-life dependencies can be reasonably accurately described by linear functions. If we want a...
International audienceNeural networks are used increasingly as statistical models. The performance o...
This dissertation is designed to answer the following questions: (1) Which measurement model is bett...
Many real-life dependencies can be reasonably accurately described by linear functions. If we want a...
The aim of this research was to compare the data analytic applicability of a backpropagated neural n...
Neural networks are being used in areas of prediction and classification, the areas where statistica...
The purpose of this paper is to compare and contrast traditional regression models with a neural net...
In this paper, Artificial Neural Networks (ANN) and Regression Analysis models were considered to de...
This research work presents new development in the field of natural science, where comparison is mad...
Introduction: Artificial neural networks mimic brains behavior. They are able to predict and feature...
The current study provides an exposition of artificial neural network (ANN) methodology in the conte...
In this paper, Artificial Neural Networks (ANN) and Regression Analysis models were considered to de...
The purpose of this paper is to compare and contrast traditional regression models with a neural net...
The current study provides an exposition of artificial neural network (ANN) methodology in the conte...
This paper gives a brief overview of artificial neural networks which may be used to model data simi...
Many real-life dependencies can be reasonably accurately described by linear functions. If we want a...
International audienceNeural networks are used increasingly as statistical models. The performance o...
This dissertation is designed to answer the following questions: (1) Which measurement model is bett...
Many real-life dependencies can be reasonably accurately described by linear functions. If we want a...