Introduction to Ensemble Learning

This paper is prepared to provide a brief introduction to the topic of Ensemble Learning. It aims to provide the reader with a broad overview on the approach of Ensemble Methods.Sections:-What is Ensemble Learning?-The Rationale Behind Ensemble Methods-Common Approaches To Ensemble Methods-Success Factors Of Ensemble Methods-Proven Applications of Ensemble Methods

[1]  Eric Bauer,et al.  An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Variants , 1999, Machine Learning.

[2]  E. Kleinberg.  An overtraining-resistant stochastic modeling method for pattern recognition , 1996 .

[3]  Eugene M. Kleinberg.  A Mathematically Rigorous Foundation for Supervised Learning , 2000, Multiple Classifier Systems.

[4]  Yoram Singer,et al.  Reducing Multiclass to Binary: A Unifying Approach for Margin Classifiers , 2000, J. Mach. Learn. Res..

[5]  Thomas G. Dietterich,et al.  Error-Correcting Output Coding Corrects Bias and Variance , 1995, ICML.

[6]  Thomas G. Dietterich.  Multiple Classifier Systems , 2000, Lecture Notes in Computer Science.

[7]  Oliver Steinki.  An investigation of ensemble methods to improve the bias and/or variance of option pricing models based on Lévy processes , 2015 .

[8]  Jiri Matas,et al.  On Combining Classifiers , 1998, IEEE Trans. Pattern Anal. Mach. Intell..

[9]  Leo Breiman,et al.  Bagging Predictors , 1996, Machine Learning.

[10]  Alípio Mário Jorge,et al.  Ensemble approaches for regression: A survey , 2012, CSUR.

[11]  L. Cooper,et al.  When Networks Disagree: Ensemble Methods for Hybrid Neural Networks , 1992 .

[12]  Robi Polikar,et al.  An ensemble based data fusion approach for early diagnosis of Alzheimer's disease , 2008, Inf. Fusion.

[13]  Fabio Roli,et al.  Methods for Designing Multiple Classifier Systems , 2001, Multiple Classifier Systems.

[14]  Yoav Freund,et al.  Experiments with a New Boosting Algorithm , 1996, ICML.

[15]  Gavin Brown,et al.  Diversity in neural network ensembles , 2004 .

[16]  Jörg D. Wichard,et al.  Building Ensembles with Heterogeneous Models , 2003 .

[17]  Lefteris Angelis,et al.  Selective fusion of heterogeneous classifiers , 2005, Intell. Data Anal..

[18]  L. Breiman.  Arcing Classifiers , 1998 .

[19]  Ching Y. Suen,et al.  Optimal combinations of pattern classifiers , 1995, Pattern Recognit. Lett..

[20]  Chris E Forest,et al.  Ensemble climate predictions using climate models and observational constraints , 2007, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[21]  David W. Aha,et al.  Ensembles of Classifiers for Morphological Galaxy Classification , 2001 .