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Figure 2: Comparison of 10 Widely Used Prediction Methods

Figure 2: Comparison of 10 Widely Used Prediction Methods
Description
Method Model performance (cross-entropy)
Boosting 0.896
Random Forests 0.892
Bagging 0.882
Support Vector Machines 0.862
Neural Networks 0.846
K-nearest Neighbors 0.815
Additive 0.791
Decision Trees 0.706
Linear Regression 0.685
Naive Bayes Classifier 0.650

For more information on these prediction models, see Caruana, Rich, and Alexandru Niculescu-Mizil, "An Empirical Comparison of Supervised Learning Algorithms Using Different Performance Metrics," in Proceedings of the 23rd International Conference on Machine Learning, New York: Association for Computing Machinery, 2006: 161–168.