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Logistic regression
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#	Item
611	Unsupervised Learning of Video Representations using LSTMs arXiv:1502.04681v1 [cs.LG] 16 Feb 2015 Nitish Srivastava Elman Mansimov Add to Reading List Source URL: arxiv.org Language: English - Date: 2015-02-16 20:34:23 Cybernetics Recurrent neural network Science Machine learning Supervised learning Decoder Logistic regression Neural networks Statistics Long short term memory
612	2010 IEEE International Conference on Data Mining A Log-Linear Model with Latent Features for Dyadic Prediction Aditya Krishna Menon Department of Computer Science and Engineering University of California, San Diego Add to Reading List Source URL: cseweb.ucsd.edu Language: English - Date: 2010-12-17 04:55:45 Regression analysis Linear algebra Matrix theory Actuarial science Categorical data Collaborative filtering Logistic regression Singular value decomposition Recommender system Statistics Algebra Mathematics
613	FACULTEIT ECONOMIE EN BEDRIJFSKUNDE TWEEKERKENSTRAAT 2 B-9000 GENT Tel. Fax. Add to Reading List Source URL: www.feb.ugent.be Language: English - Date: 2012-06-18 04:43:21 Business intelligence Statistical models Customer attrition Predictive analytics Dummy variable Linear regression Logistic regression RFM Churn rate Statistics Regression analysis Econometrics
614	Building General Random Effect Models with R and ADMB Jeff Laake, Hans Skaug and Devin Johnson January 23, 2013 The ADMB and Otter Research web sites provide examples of specific random effect models. See http://admb-pro Add to Reading List Source URL: www.admb-project.org Language: English - Date: 2013-01-23 19:07:30 ADMB Cross-platform software Free statistical software Mixed model Logistic regression Random variable Normal distribution Mixed logit Exponential random graph models Statistics Regression analysis Probability theory
615	6.867 Machine learning, lecture 4 (Jaakkola) 1 The Support Vector Machine and regularization We proposed a simple relaxed optimization problem for ﬁnding the maximum margin sep Add to Reading List Source URL: ocw.mit.edu Language: English - Date: 2015-03-15 16:36:56 M-estimators Regression analysis Econometrics Maximum likelihood Loss function Likelihood function Logistic function Logistic regression Regularization Statistics Estimation theory Statistical theory
616	Chapter 3 Factors associated with job satisfaction amongst Australian university academics and future workforce implications Peter Bentley, Hamish Coates, Ian Dobson, Leo Goedegebuure, & V. Lynn Meek P. Bentley, L. Goede Add to Reading List Source URL: www.lhmartininstitute.edu.au Language: English - Date: 2014-11-11 19:38:19 Organizational behavior Two-factor theory Factor analysis Motivation Logistic regression Linear regression Statistics Regression analysis Job satisfaction
617	Interaction Significant, Simple Main Effects Not Significant A sports psychologist at a French university, wrote me for advice about a binary logistic regression. The outcome variable was whether or not the subject ha Add to Reading List Source URL: core.ecu.edu Language: English - Date: 2011-01-17 15:52:15 Medical statistics Epidemiology Analysis of variance Interaction Pharmacology Gender role Odds ratio Girl Statistics Gender Behavior
618	Package ‘BMA’ February 19, 2015 VersionDateTitle Bayesian Model Averaging Author Adrian Raftery <>, Jennifer Hoeting, Add to Reading List Source URL: cran.r-project.org Language: English - Date: 2015-02-19 03:23:58 Estimation theory Bayesian inference Statistical models Dummy variable Parameter Logistic regression Economic model Linear regression Bayes factor Statistics Regression analysis Econometrics
619	YI ZHAO, YING ZHAO, and INSEONG SONG* Recent studies in marketing have consistently shown that all customers are not equally profitable. In the credit card business, all customers are not equally risky. When a customer m Add to Reading List Source URL: www.bm.ust.hk Language: English - Date: 2012-04-05 01:25:56 Credit bureau Credit history Merchant account Market segmentation Logistic regression Credit risk Financial economics Credit Credit card
620	Forecasting a Moving Target: Ensemble Models for ILI Case Count Predictions Prithwish Chakraborty Aravindan Mahendiran Sumiko R Mekaru§ ∗† Add to Reading List Source URL: people.cs.vt.edu Language: English - Date: 2014-04-11 14:34:12 Econometrics Categorical data Estimation theory Linear regression Kalman filter Logistic regression Cross-validation Flu pandemic Count data Statistics Regression analysis Data analysis

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