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Model selection
Results: 1077

#	Item
71	The Cassiopeia Model: A study with other algorithms for attribute selection in text clusterization. Marcus V. C. Guelpeli Ana Cristina Bicharra Garcia 1 Departamento de Ciência da Computação Universidade Federal Flumi Add to Reading List Source URL: www.di.fc.ul.pt Language: English - Date: 2016-05-03 08:03:56 Computational linguistics Natural language processing Data mining Artificial intelligence applications Statistical natural language processing Automatic summarization Cluster analysis Stop words Language identification Tfidf Resource Description Framework Text corpus
72	On a model of portfolio selection with benchmark Received (in revised form): 19th October, 2001 Niklas Wagner is a lecturer in Finance at Munich University of Technology, Germany. He received a PhD in Finance from Augsbu Add to Reading List Source URL: www.wiwi.uni-passau.de Language: English - Date: 2010-04-05 09:26:12 Mathematical finance Financial risk Decision theory Financial economics Investment Portfolio optimization Harry Markowitz Tracking error Modern portfolio theory Hyperbolic absolute risk aversion Beta Asset allocation
73	Differential Dementia Diagnosis on Incomplete Data with Latent Trees Christian Ledig1 , Sebastian Kaltwang1 , Antti Tolonen2 , Juha Koikkalainen3 , Philip Scheltens4 , Frederik Barkhof4 , Hanneke Rhodius-Meester4 , Betty Add to Reading List Source URL: ibug.doc.ic.ac.uk Language: English - Date: 2016-07-01 12:05:05 Machine learning Statistical analysis Statistical classification Statistical models Model selection Imputation Support vector machine Cross-validation Mixture model Data analysis Standard deviation Outlier
74	Mgmt 469 Model Specification: Choosing the Right Variables for the Right Hand Side Even if you have only a handful of predictor variables to choose from, there are infinitely many ways to specify the right hand side of a Add to Reading List Source URL: www.kellogg.northwestern.edu Language: English - Date: 2008-03-12 14:38:04 Regression analysis Multicollinearity Variance inflation factor Dummy variable Interaction Omitted-variable bias Dependent and independent variables Categorical variable Linear regression Spike-and-slab variable selection
75	SYSTEMATIC SELECTION OF VERY IMPORTANT POINTS (VIP) FROM DIGITAL TERRAIN MODEL FOR CONSTRUCTING TRIANGULAR IRREGULAR NETWORKS Zi-Tan Chen and J. Armando Guevara Environmental Systems Research Institute 380 New York Stree Add to Reading List Source URL: mapcontext.com Language: English - Date: 2008-08-30 00:30:22 Image processing Digital imaging Digital photography Computer graphics Digital geometry Pixel Triangulated irregular network Image resolution Pixel artist
76	What matters: Size does, Smarts Don’t Albrecht Zimmermann and Bj¨orn Bringmann Department of Computer Science, Katholieke Universiteit Leuven, Celestijnenlaan 200A, 3001 Leuven, Belgium {Albrecht.Zimmermann,Bjorn.Brin Add to Reading List Source URL: www.ke.tu-darmstadt.de Language: English - Date: 2009-11-06 11:55:58 Model selection Machine learning Formal sciences Statistical classification Cross-validation Support vector machine Data mining Feature selection DM
77	IMPROVING MOVING MAPS: A SYSTEM FOR FEATURE SELECTION BASED ON A NEW COGNITIVE MODEL Paul Van Zuyle Dept. of Geography University of California Santa Barbara, CA 93106 Add to Reading List Source URL: mapcontext.com Language: English - Date: 2008-08-29 22:36:32 Cartography Cartographic generalization Generalization Topological map Map Geographic information system Level of detail Distance Scale Conceptual model
78	Combining Machine Learning with Evolutionary Computation: Recent Results on LEM Guido Cervone Ryszard S. Michalski* Kenneth K. Kaufman Liviu A. Panait Add to Reading List Source URL: cervone.psu.edu Language: English - Date: 2015-11-18 09:12:45 Cybernetics Evolution Mathematical optimization Learnable Evolution Model Genetic algorithm Evolutionary computation Evolutionary algorithm Ryszard S. Michalski Rosenbrock function Natural selection Machine learning
79	Dear GEMS users, Discussions with and feedback from GEMS users revealed to us that some users use the system for analysis of extremely small sample datasets. A good heuristic rule for defining extremely small Add to Reading List Source URL: www.gems-system.org Language: English - Date: 2005-10-21 16:55:14 Statistical inference Estimation theory Cross-validation Machine learning Model selection Statistics Estimator Variance Resampling
80	IEEE TRANSACTIONS ON SOFTWARE ENGINEERING 1 An Empirical Comparison of Model Validation Techniques for Defect Prediction Models Add to Reading List Source URL: chakkrit.com Language: English - Date: 2016-08-10 02:46:52 Machine learning Computational statistics Statistical inference Regression analysis Model selection Cross-validation Bootstrapping Bootstrap aggregating Logistic regression Overfitting Statistics Autoregressive model

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