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Logistic regression
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211	Title stata.com mi impute logit — Impute using logistic regression Description Add to Reading List Source URL: www.stata.com Language: English - Date: 2015-04-07 21:48:26
212	Efficient L1 Regularized Logistic Regression Su-In Lee, Honglak Lee, Pieter Abbeel and Andrew Y. Ng Computer Science Department Stanford University Stanford, CA 94305 Add to Reading List Source URL: homes.cs.washington.edu Language: English - Date: 2010-01-10 06:26:49
213	Leukemia Prediction Using Sparse Logistic Regression Tapio Manninen1, Heikki Huttunen1, Pekka Ruusuvuori1, Matti Nykter2 1 Department of Signal Processing, Tampere University of Technology, Tampere, Finland, 2 Institute Add to Reading List Source URL: www.cs.tut.fi Language: English* - Date: 2013-09-04 02:54:09
214	0.1 logit.bayes: Bayesian Logistic Regression Logistic regression specifies a dichotomous dependent variable as a function of a set of explanatory variables using a random walk Metropolis algorithm. For a maximum likeli Add to Reading List Source URL: perso.md2t.eu Language: English
215	MODEL SELECTION WITH SNML IN LOGISTIC REGRESSION Antti Liski1 , Ioan Tabus2 and Reijo Sund3 1 Department of Signal Processing, Tampere University of Technology, P.O.Box 553, FINTampere, FINLAND, Add to Reading List Source URL: sp.cs.tut.fi Language: English - Date: 2009-08-14 05:54:20
216	Statistical Learning, FallAssignment 2: Classification The purpose of this exercise is to compare the Naive Bayes (NB) model to Logistic Regression (LR) on data with categorical attributes. We will first train/fit Add to Reading List Source URL: www.timvanerven.nl Language: English - Date: 2014-12-05 11:38:24 Econometrics Actuarial science Statistical classification Naive Bayes classifier Training set Logistic regression Overfitting Generalized linear model Supervised learning Statistics Regression analysis Machine learning
217	Technical Guide for Latent GOLD Choice 4.0: Basic and Advanced1 Jeroen K. Vermunt and Jay Magidson Add to Reading List Source URL: www.statisticalinnovations.com Language: English - Date: 2009-05-15 13:36:36 Econometrics Categorical data Statistical models Discrete choice Multinomial logit Latent class model Linear regression Logistic regression Logit Statistics Economics Regression analysis
218	An ensemble of classiﬁers approach with multiple sources of information Roberto Santana, Concha Bielza, Pedro Larrañaga Departamento de Inteligencia Artiﬁcial, Universidad Politécnica de Madrid roberto.santana@upm. Add to Reading List Source URL: www.cis.hut.fi Language: English - Date: 2012-01-05 06:58:35 Machine learning Econometrics Covariance and correlation Correlation and dependence Feature selection Decision tree learning Cross-validation Logistic regression Statistics Regression analysis Model selection
219	Automatic Detection and Classification of Prosodic Events Andrew Rosenberg Submitted in partial fulfillment of the Requirements for the degree of Doctor of Philosophy Add to Reading List Source URL: www.cs.columbia.edu Language: English - Date: 2009-07-21 11:55:29 Phonetics Prosody Corpus linguistics Pitch accent Part-of-speech tagging Logistic regression ToBI Stress Regression analysis Linguistics Phonology Tone
220	Technical Guide for Latent GOLD Choice 4.0: Basic and Advanced1 Jeroen K. Vermunt and Jay Magidson Add to Reading List Source URL: statisticalinnovations.com Language: English - Date: 2009-05-15 16:09:58 Econometrics Categorical data Statistical models Discrete choice Multinomial logit Latent class model Linear regression Logistic regression Logit Statistics Economics Regression analysis

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