A comparative predictive analysis of neural networks (NNs), nonlinear regression and classification and regression tree (CART) models
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[1] Comparison Levine,et al. Quantitative Applications in the Social Sciences , 2006 .
[2] Wei Zhang,et al. Neural Network Earnings per Share Forecasting Models: A Comparative Analysis of Alternative Methods , 2004, Decis. Sci..
[3] Leo Breiman,et al. Stacked regressions , 2004, Machine Learning.
[4] G. Vozikis,et al. Improving Health Care Organizational Management Through Neural Network Learning , 2002, Health care management science.
[5] Fatemeh Zahedi,et al. Leveraging the Strengths of Choice Models and Neural Networks: A Multiproduct Comparative Analysis , 2002, Decis. Sci..
[6] Chang-Xue Feng,et al. Digitizing uncertainty modeling for reverse engineering applications: regression versus neural networks , 2002, J. Intell. Manuf..
[7] C.-X. J. Feng,et al. Experimental study of the effect of digitizing parameters on digitizing uncertainty with a CMM , 2002 .
[8] Nghiep Nguyen,et al. Predicting Housing Value: A Comparison of Multiple Regression Analysis and Artificial Neural Networks , 2001 .
[9] Victor L. Berardi,et al. Time series forecasting with neural network ensembles: an application for exchange rate prediction , 2001, J. Oper. Res. Soc..
[10] J S Shang,et al. Diagnosis of MRSA with neural networks and logistic regression approach , 2000, Health care management science.
[11] Richard G. Mathieu,et al. Kanban setting through artificial intelligence: a comparative study of artificial neural networks and decision trees , 2000 .
[12] Min-Yang Yang,et al. Improved neural network model for reverse engineering , 2000 .
[13] Prasad K. Yarlagadda,et al. Prediction of die casting process parameters by using an artificial neural network model for zinc alloys , 2000 .
[14] Robert Groth,et al. Data Mining: Building Competitive Advantage , 1999 .
[15] M. Mojirsheibani. Combining Classifiers via Discretization , 1999 .
[16] D. K. Harrison,et al. Improving error compensation via a fuzzy-neural hybrid model , 1999 .
[17] Whitecotton,et al. Improving Predictive Accuracy with a Combination of Human Intuition and Mechanical Decision Aids. , 1998, Organizational behavior and human decision processes.
[18] David W. Coit,et al. STATIC NEURAL NETWORK PROCESS MODELS : CONSIDERATIONS AND CASE STUDIES , 1998 .
[19] Victor L. Berardi,et al. An investigation of neural networks in thyroid function diagnosis , 1998, Health care management science.
[20] H. Chipman,et al. Bayesian CART Model Search , 1998 .
[21] Christopher R. Westphal,et al. Data Mining Solutions: Methods and Tools for Solving Real-World Problems , 1998 .
[22] Bopaya Bidanda,et al. A neural network process model for abrasive flow machining operations , 1998 .
[23] R. D. Hurrion,et al. An example of simulation optimisation using a neural network metamodel: finding the optimum number of kanbans in a manufacturing system , 1997 .
[24] Patrick L. Brockett,et al. A Comparative Analysis of Neural Networks and Statistical Methods for Predicting Consumer Choice , 1997 .
[25] Alice E. Smith,et al. COST ESTIMATION PREDICTIVE MODELING: REGRESSION VERSUS NEURAL NETWORK , 1997 .
[26] Suck-Joo Na,et al. Optimum design based on mathematical model and neural network to predict weld parameters for fillet joints , 1997 .
[27] R. Tibshirani,et al. Combining Estimates in Regression and Classification , 1996 .
[28] Brad Warner,et al. Understanding Neural Networks as Statistical Tools , 1996 .
[29] Kishan G. Mehrotra,et al. Elements of artificial neural networks , 1996 .
[30] W. Bruce Croft,et al. Combining classifiers in text categorization , 1996, SIGIR '96.
[31] W. Vach,et al. Neural networks and logistic regression: Part I , 1996 .
[32] Marimuthu Palaniswami,et al. A hybrid neural approach to combinatorial optimization , 1996, Comput. Oper. Res..
[33] Akhil Kumar,et al. An empirical comparison of neural network and logistic regression models , 1995 .
[34] S. H. Huang,et al. Applications of neural networks in manufacturing: a state-of-the-art survey , 1995 .
[35] Brian D. Ripley,et al. Neural Networks and Related Methods for Classification , 1994 .
[36] Alice E. Smith,et al. Reducing waste in casting with a predictive neural model , 1994, J. Intell. Manuf..
[37] Nallan C. Suresh,et al. Performance of Selected Part‐Machine Grouping Techniques for Data Sets of Wide Ranging Sizes and Imperfection , 1994 .
[38] Laurene V. Fausett,et al. Fundamentals Of Neural Networks , 1994 .
[39] William Remus,et al. Neural network models for intelligent support of managerial decision making , 1994, Decis. Support Syst..
[40] John Mingers,et al. Neural Networks, Decision Tree Induction and Discriminant Analysis: an Empirical Comparison , 1994 .
[41] Charles M. Bachmann,et al. Neural Networks and Their Applications , 1994 .
[42] James M. Hutchinson,et al. A radial basis function approach to financial time series analysis , 1993 .
[43] James A. Freeman,et al. Simulating neural networks - with Mathematica , 1993 .
[44] Harald Hruschka,et al. Determining market response functions by neural network modeling: A comparison to econometric techniques , 1993 .
[45] Donald E. Brown,et al. A comparison of decision tree classifiers with backpropagation neural networks for multimodal classification problems , 1992, Pattern Recognit..
[46] Murray Smith,et al. Neural Networks for Statistical Modeling , 1993 .
[47] Fred Y. Wu,et al. Applications of neural network in regression analysis , 1992 .
[48] Herbert Moskowitz,et al. Integrating Neural Networks and Semi‐Markov Processes for Automated Knowledge Acquisition: An Application to Real‐time Scheduling* , 1992 .
[49] Halbert White,et al. Artificial Neural Networks: Approximation and Learning Theory , 1992 .
[50] J. Neter,et al. Applied Linear Statistical Models (3rd ed.). , 1992 .
[51] TamKar Yan,et al. Managerial Applications of Neural Networks , 1992 .
[52] Melody Y. Kiang,et al. Managerial Applications of Neural Networks: The Case of Bank Failure Predictions , 1992 .
[53] Adam Krzyżak,et al. Methods of combining multiple classifiers and their applications to handwriting recognition , 1992, IEEE Trans. Syst. Man Cybern..
[54] David H. Wolpert,et al. Stacked generalization , 1992, Neural Networks.
[55] H Fujita,et al. Application of artificial neural network to computer-aided diagnosis of coronary artery disease in myocardial SPECT bull's-eye images. , 1992, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.
[56] Anders Krogh,et al. Introduction to the theory of neural computation , 1994, The advanced book program.
[57] Riccardo Poli,et al. A neural network expert system for diagnosing and treating hypertension , 1991, Computer.
[58] Paul J. Werbos,et al. Links Between Artificial Neural Networks (ANN) and Statistical Pattern Recognition , 1991 .
[59] Anil K. Jain,et al. Artificial neural networks and statistical pattern recognition : old and new connections , 1991 .
[60] Wray L. Buntine,et al. Bayesian Back-Propagation , 1991, Complex Syst..
[61] William G. Baxt,et al. Use of an Artificial Neural Network for Data Analysis in Clinical Decision-Making: The Diagnosis of Acute Coronary Occlusion , 1990, Neural Computation.
[62] D. Hosmer,et al. Applied Logistic Regression , 1991 .
[63] T. Sejnowski,et al. Predicting the secondary structure of globular proteins using neural network models. , 1988, Journal of molecular biology.
[64] H. Riedwyl,et al. Multivariate Statistics: A Practical Approach , 1988 .
[65] R. Lippmann,et al. An introduction to computing with neural nets , 1987, IEEE ASSP Magazine.
[66] A. H. Studenmund. Using Econometrics: A Practical Guide , 1987 .
[67] Geoffrey E. Hinton,et al. Learning representations by back-propagating errors , 1986, Nature.
[68] R. H. Myers. Classical and modern regression with applications , 1986 .
[69] Leo Breiman,et al. Classification and Regression Trees , 1984 .
[70] S. J. Press,et al. Choosing between Logistic Regression and Discriminant Analysis , 1978 .
[71] Ross L. Watts,et al. TIME-SERIES OF ANNUAL ACCOUNTING EARNINGS , 1977 .
[72] V. Barnett,et al. Applied Linear Statistical Models , 1975 .
[73] M. Stone. Cross‐Validatory Choice and Assessment of Statistical Predictions , 1976 .
[74] Richard O. Duda,et al. Pattern classification and scene analysis , 1974, A Wiley-Interscience publication.
[75] G. W. Snedecor. STATISTICAL METHODS , 1967 .