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Decision tree learning
Results: 321

#	Item
281	Data analysis of examination papers Nikola Kaspříková, FIS VŠE & 1. LF UK Agenda & introductory comments Add to Reading List Source URL: skola.tulipany.cz Language: English - Date: 2011-06-08 17:40:06 Actuarial science Regression analysis Data analysis Decision tree learning Statistics Econometrics Science
282	Microsoft PowerPoint - dtree18.ppt Add to Reading List Source URL: www.autonlab.org Language: English - Date: 2008-07-07 16:16:17 Computer data Machine learning Decision theory Decision tree Contingency table Copyright law of the United States Attribute Overfitting Data set Statistics Data Information
283	Privacy Preserving Data Mining∗ Yehuda Lindell Department of Computer Science Weizmann Institute of Science Rehovot, Israel. [removed] Add to Reading List Source URL: www.pinkas.net Language: English - Date: 2004-02-17 13:42:09 Decision trees Theoretical computer science Secure multi-party computation ID3 algorithm Decision tree learning ID3 Secure two-party computation Communication complexity Oblivious transfer Cryptographic protocols Data Information
284	Scoring: The Next Breakthrough in Microcredit? Paper prepared for the Consultative Group to Assist the Poorest Mark Schreiner1 June 11, 2002 Microfinance Risk Management 6970 Chippewa St. #1W, St. Louis, MO[removed], U Add to Reading List Source URL: www.microfinance.com Language: English - Date: 2013-08-10 21:21:57 Microfinance Ethics Social economy Business intelligence Microcredit United Nations Secretariat Decision tree learning Vulnerability Risk Development Statistics Management
285	Learning from Heterogeneous Sources via Gradient Boosting Consensus Xiaoxiao Shi∗ Abstract Jean-Francois Paiement† Add to Reading List Source URL: david.grangier.info Language: English - Date: 2012-01-08 20:04:39 Decision trees Supervised learning Database Cross-validation Decision tree learning Graph Gradient boosting Flow network Geographic information system Statistics Machine learning Graph theory
286	GBC: Gradient Boosting Consensus Model for Heterogeneous Data Xiaoxiao Shi∗ Jean-Francois Paiement† Add to Reading List Source URL: david.grangier.info Language: English - Date: 2014-05-19 17:20:06 Supervised learning Gradient boosting Decision tree learning Graph Database Geographic information system Cross-validation Learning to rank Flow network Machine learning Artificial intelligence Computational statistics
287	Non asymptotic risk bounds for Classification And Regression Trees (CART) classifiers are obtained in the binary supervised classification framework under a margin assumption on the joint distribution of the covariates a Add to Reading List Source URL: www.medical-science.site88.net Language: English - Date: 2013-01-31 20:56:24 Computational statistics Learning Pruning Tree Decision tree learning Supervised learning Statistical classification Binary tree Machine learning Decision trees Artificial intelligence
288	Tree Based Hierarchical Reinforcement Learning William T. B. Uther August 2002 CMU-CS[removed] Add to Reading List Source URL: reports-archive.adm.cs.cmu.edu Language: English - Date: 2003-03-11 11:32:52 Mathematical logic Theoretical computer science Markov decision process Reinforcement learning Abstraction Problem solving Statistics Mind Algorithm
289	Nonparametric Forecasting of the Manufacturing Output Growth with Firm-level Survey Data c ` G´erard BIAU a , Olivier BIAU b , and Laurent ROUVIERE Add to Reading List Source URL: www.ensai.fr Language: English - Date: 2013-01-23 11:12:31 Dimension reduction Data mining Data analysis Ensemble learning Random forest Regression analysis Decision tree learning XT Sample Statistics Machine learning Decision trees
290	An Extension of the CHAID Tree-based Segmentation Algorithm to Multiple Dependent Variables Jay Magidson1 and Jeroen K. Vermunt2 1 2 Add to Reading List Source URL: www.statisticalinnovations.com Language: English - Date: 2009-01-30 12:07:07 Econometrics Categorical data Psychometrics CHAID Latent class model Multinomial logit Decision tree learning Latent variable Factor analysis Statistics Regression analysis Decision trees