Ensemble learning

Results: 532



#Item
251Ensemble learning / Supervised learning / Multi-label classification / Multiclass classification / Regression analysis / Feature selection / Boosting / Correlation and dependence / Classifier chains / Statistics / Machine learning / Statistical classification

Mach Learn manuscript No. (will be inserted by the editor) Efficient Max-Margin Multi-Label Classification with Applications to Zero-Shot Learning Bharath Hariharan · S. V. N. Vishwanathan ·

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Source URL: www.cs.berkeley.edu

Language: English - Date: 2012-04-02 22:06:30
252Decision trees / Ensemble learning / Random forest / Linear regression / Predictive Model Markup Language / Decision tree learning / Statistics / Regression analysis / Econometrics

Bachelorarbeit Decision Forests for Regression Moritz Einfalt[removed]

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Source URL: www.multimedia-computing.de

Language: English - Date: 2014-12-02 06:09:53
253Learning / Bayesian statistics / Ensemble learning / Naive Bayes classifier / Random forest / Motion Picture Association of America film rating system / Trailer / Pattern recognition / Support vector machine / Statistics / Statistical classification / Machine learning

1 Film Classification by Trailer Features Edmund Helmer and Qinghui Ji December 14, 2012

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Source URL: cs229.stanford.edu

Language: English - Date: 2013-01-09 19:55:28
254Statistical classification / Learning / Machine learning / AdaBoost / Linear classifier / Onset / Support vector machine / Classifier / Boosting / Statistics / Ensemble learning / Artificial intelligence

¨t Augsburg Universita Note onset detection for the transcription of polyphonic piano music C. G. v. d. Boogaart, R. Lienhart

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Source URL: www.multimedia-computing.de

Language: English - Date: 2011-06-17 18:01:46
255Support vector machine / Gain / Biology / Science / Information / Protein domain / Protein structure / Ensemble learning

Multi-Domain Learning: When Do Domains Matter? Mark Dredze Mahesh Joshi School of Computer Science Human Language Technology Center of Excellence Johns Hopkins University Carnegie Mellon University

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Source URL: www.cs.cmu.edu

Language: English - Date: 2012-06-18 14:25:32
256Learning / Ensemble learning / Support vector machine / Multiclass classification / Perceptron / Hinge loss / AdaBoost / Cross-validation / Statistics / Machine learning / Statistical classification

Multiclass Boosting with Hinge Loss based on Output Coding Tianshi Gao Electrical Engineering Department, Stanford, CA[removed]USA Daphne Koller Computer Science Department, Stanford, CA[removed]USA

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Source URL: ai.stanford.edu

Language: English - Date: 2012-08-02 01:49:01
257Computational statistics / Data mining / Concept drift / Statistical classification / Ensemble learning / Supervised learning / Spam / Classifier / Support vector machine / Statistics / Machine learning / Internet

A Comparison of Ensemble and Case-Base Maintenance Techniques for Handling Concept Drift in Spam Filtering

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Source URL: aaai.org

Language: English - Date: 2006-07-07 02:48:27
258Boosting / Gradient boosting / AdaBoost / Logistic regression / Quantile regression / Least squares / Proportional hazards models / Statistics / Regression analysis / Ensemble learning

Package ‘gbm’ February 19, 2015 Version 2.1 Date 2013-05-10 Title Generalized Boosted Regression Models Author Greg Ridgeway with contributions from

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Source URL: kambing.ui.ac.id

Language: English - Date: 2015-02-19 17:55:09
259Machine learning / Ensemble learning / Statistical classification / Co-training / Support vector machine / Linear classifier / AdaBoost / Document classification / Boosting / Artificial intelligence / Statistics / Computational statistics

IDENTIFYING FLUORESCENCE MICROSCOPE IMAGES IN ONLINE JOURNAL ARTICLES USING BOTH IMAGE AND TEXT FEATURES Juchang Hua1,2,4, Orhan N. Ayasli5, William W. Cohen1,4 and Robert F. Murphy1,2,3,5 Center for Bioimage Informatics

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Source URL: www.cs.cmu.edu

Language: English - Date: 2007-04-16 09:36:09
260Statistics / Vision / Image processing / Ensemble learning / Histogram of oriented gradients / Segmentation / Linear classifier / Color histogram / Random forest / Computer vision / Artificial intelligence / Machine learning

Object Class Segmentation using Random Forests F. Schroff1 , A. Criminisi2 , A. Zisserman1 1 Dept. of Engineering Science, University of Oxford {schroff,az}@robots.ox.ac.uk 2 Microsoft Research Ltd., [removed]

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Source URL: www.bmva.org

Language: English - Date: 2012-02-07 06:35:38
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