
This Article  
 
Share  
Bibliographic References  
Add to:  
Digg Furl Spurl Blink Simpy Del.icio.us Y!MyWeb  
Search  
 
ASCII Text  x  
Ronaldo C. Prati, Gustavo E.A.P.A. Batista, Maria Carolina Monard, "A Survey on Graphical Methods for Classification Predictive Performance Evaluation," IEEE Transactions on Knowledge and Data Engineering, vol. 23, no. 11, pp. 16011618, November, 2011.  
BibTex  x  
@article{ 10.1109/TKDE.2011.59, author = {Ronaldo C. Prati and Gustavo E.A.P.A. Batista and Maria Carolina Monard}, title = {A Survey on Graphical Methods for Classification Predictive Performance Evaluation}, journal ={IEEE Transactions on Knowledge and Data Engineering}, volume = {23}, number = {11}, issn = {10414347}, year = {2011}, pages = {16011618}, doi = {http://doi.ieeecomputersociety.org/10.1109/TKDE.2011.59}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }  
RefWorks Procite/RefMan/Endnote  x  
TY  JOUR JO  IEEE Transactions on Knowledge and Data Engineering TI  A Survey on Graphical Methods for Classification Predictive Performance Evaluation IS  11 SN  10414347 SP1601 EP1618 EPD  16011618 A1  Ronaldo C. Prati, A1  Gustavo E.A.P.A. Batista, A1  Maria Carolina Monard, PY  2011 KW  Machine learning KW  data mining KW  performance evaluation KW  ROC curves KW  cost curves KW  lift graphs. VL  23 JA  IEEE Transactions on Knowledge and Data Engineering ER   
[1] C. Schaffer, "A Conservation Law for Generalization Performance," Proc. 11th Int'l Conf. Machine Learning (ICML '94), pp. 259265, 1994.
[2] D.H. Wolpert, "The Lack of a Priori Distinctions between Learning Algorithms," Neural Computation, vol. 8, pp. 13411390, 1996.
[3] P. Brazdil, C. GiraudCarrier, C. Soares, and R. Vilalta, Metalearning: Applications to Data Mining. Springer, 2009.
[4] A.M. Martínez and M. Zhu, "Where are Linear Feature Extraction Methods Applicable?" IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 27, no. 12, pp. 19341944, Dec. 2005.
[5] M. Zhu and A.M. Martínez, "Subclass Discriminant Analysis," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 28, no. 8, pp. 12741286, Aug. 2006.
[6] F.J. Provost, T. Fawcett, and R. Kohavi, "The Case against Accuracy Estimation for Comparing Induction Algorithms," Proc. 15th Int'l Conf. Machine Learning (ICML '98), pp. 445453, 1998.
[7] J.C. Xue and G.M. Weiss, "Quantification and SemiSupervised Classification Methods for Handling Changes in Class Distribution," Proc. 15th ACM SIGKDD Int'l Conf. Knowledge Discovery and Data Mining (KDD '09). pp. 897906, 2009.
[8] D.J. Hand, "Measuring Classifier Performance: A Coherent Alternative to the Area under the Roc Curve," Machine Learning, vol. 77, no. 1, pp. 103123, 2009.
[9] P. Datta, "Business Focused Evaluation Methods: A Case Study," Proc. Third European Conf. Principles of Data Mining and Knowledge Discovery (PKDD '99), pp. 316322, 1999.
[10] C. Drummond, W. Elazmeh, N. Japkowicz, and P. Cochairs, "2006 AAAI Workshop Evaluation Methods for Machine Learning," Technical Report WS0606, AAAI press, 2006.
[11] C. Drummond, W. Elazmeh, N. Japkowicz, and S.A. Macskassy, "2007 AAAI Workshop Evaluation Methods for Machine Learning II," Technical Report WS0705, AAAI Press, 2007.
[12] W. Klement, C. Drummond, N. Japkowicz, and S. Macskassy, "The Third Workshop Evaluation Methods for Machine Learning," http://www.site.uottawa.ca/ICML09WSindex.html , 2008.
[13] W. Klement, C. Drummond, N. Japkowicz, and S. Macskassy, "The Fourth Workshop Evaluation Methods for Machine Learning," Proc. 26th Ann. Int'l Conf. Machine Learning (ICML '09), http://www.site.uottawa.ca/ICML09WSindex.html , 2009.
[14] C. Drummond, "Machine Learning as an Experimental Science (Revisited)," Proc. AAAI Workshop Evaluation Methods for Machine Learning (Technical Report WS0606), 2006.
[15] C. Drummond and N. Japkowicz, "Warning: Statistical Benchmarking is Addictive. Kicking the Habit in Machine Learning," J. Experimental and Theoretical Artificial Intelligence, vol. 22, no. 1, pp. 6780, 2009.
[16] J. Davis and M. Goadrich, "The Relationship between PrecisionRecall and ROC Curves," Proc. 23rd Int'l Conf. Machine Learning (ICML '06), pp. 233240, 2006.
[17] T. Fawcett, "An Introduction to ROC Analysis," Pattern Recognition Letters, vol. 27, no. 8, pp. 861874, 2006.
[18] M.C. Monard and G.E.A.P.A. Batista, "Graphical Methods for Classifier Performance Evaluation," Proc. Advances in Logic, Artificial Intelligence and Robotics (LAPTEC '2003), pp. 5967, 2003.
[19] C. Drummond and R.C. Holte, "Cost Curves: An Improved Method for Visualizing Classifier Performance," Machine Learning, vol. 65, no. 1, pp. 95130, 2006.
[20] L. Torgo and J. Gama, "Regression Using Classification Algorithms," Intelligent Data Analysis, vol. 1, nos. 14, pp. 275292, 1997.
[21] S. Rosset, C. Perlich, and B. Zadrozny, "RankingBased Evaluation of Regression Models," Knowledge and Information Systems, vol. 12, no. 3, pp. 331353, 2007.
[22] K.A. Toh and H.L. Eng, "Between ClassificationError Approximation and Weighted LeastSquares Learning," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 30, no. 4, pp. 658669, Apr. 2008.
[23] L. Breiman, J. Friedman, R. Olshen, and C. Stone, Classification and Regression Trees. Wadsworth Int'l Group, 1984.
[24] C. Elkan, "The Foundations of CostSensitive Learning," Proc. 17th Int'l Joint Conf. Artificial Intelligence (IJCAI '01), pp. 973978, 2001.
[25] P. Domingos, "Metacost: A General Method for Making Classifiers CostSensitive," Proc. Fifth ACM SIGKDD Int'l Conf. Knowledge Discovery and Data Mining (KDD '99), pp. 155164, 1999.
[26] A.P. Bradley, "The Use of the Area under the ROC Curve in the Evaluation of Machine Learning Algorithms," Pattern Recognition, vol. 30, no. 7, pp. 11451159, 1997.
[27] N.M. Adams and D.J. Hand, "Comparing Classifiers When the Misallocation Costs are Uncertain," Pattern Recognition, vol. 32, no. 7, pp. 11391147, 1999.
[28] C.X. Ling and C. Li, "Data Mining for Direct Marketing: Problems and Solutions," Proc. Fourth Int'l Conf. Knowledge Discovery and Data Mining (KDD '98), pp. 7379, 1998.
[29] G.W. Brier, "Verification of Forecasts Expressed in Terms of Probability," Monthly Weather Rev., vol. 78, no. 1, pp. 13, 1950.
[30] A.H. Murphy, "A New Vector Partition of the Probability Forecasts," J. Applied Meteorology, vol. 12, no. 4, pp. 595560, 1976.
[31] I. Cohen and M. Goldszmidt, "Properties and Benefits of Calibrated Classifiers," Proc. Eighth European Conf. Principles and Practice of Knowledge Discovery in Databases (PKDD '04), pp. 125136, 2004.
[32] W. Hsu and A.H. Murphy, "The Attributes Diagram: A Geometrical Framework for Assessing the Quality of Probability Forecasts," Int'l J. Forecasting, vol. 2, no. 3, pp. 285293, 1986.
[33] D.S. Wilks, Statistical Methods in the Atmospheric Sciences, second ed. Elsevier, 2006.
[34] T.M. Hamill, "Reliability Diagrams for Multicategory Probabilistic Forecasts," Weather and Forecasting, vol. 12, no. 4, pp. 736741, 1996.
[35] D. Mossman, "ThreeWay ROCs," Medical Decision Making, vol. 19, no. 1, pp. 7889, 1999.
[36] T.C. Landgrebe and R.P. Duin, "Efficient Multiclass ROC: Approximation by Decomposition via Confusion Matrix Perturbation Analysis," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 30, no. 5, pp. 810822, May 2008.
[37] P. van der Putten and M. van Someren, Eds., CoIL Challenge 2000: The Insurance Company Case. Published by Sentient Machine Research, http://www.liacs.nl/~putten/librarycc2000 /, 2000.
[38] I.H. Witten and E. Frank, Data Mining: Practical Machine Learning Tools and Techniques, second ed. Morgan Kaufmann, 2005.
[39] R.R. Bouckaert, "Bayesian Networks in Weka," Technical Report 14/2004, Computer Science Dept., Univ. of Waikato, 2004.
[40] R. Kohavi, "Scaling up the Accuracy of Naïve Bayes Classifiers: A DecisionTree Hybrid," Proc. Second Int'l Conf. Knowledge Discovery and Data Mining (KDD '96), pp. 202207, 1996.