搜索结果: 1-13 共查到“管理学 logistic regression”相关记录13条 . 查询时间(0.143 秒)
Support Vector Machines,Kernel Logistic Regression,and Boosting
Support Vector Machines Kernel Logistic Regression Boosting
2015/8/21
Support Vector Machines,Kernel Logistic Regression,and Boosting.
An Interior-Point Method for Large-Scale l1-Regularized Logistic Regression
logistic regression feature selection regularization regularization path
2015/7/10
Logistic regression with l1 regularization has been proposed as a promising method for feature selection in classification problems. In this paper we describe an efficient interior-point method for so...
Robust Logistic Regression using Shift Parameters
Robust Logistic Regression Shift Parameters
2013/6/17
Annotation errors can significantly hurt classifier performance, yet datasets are only growing noisier with the increased use of Amazon Mechanical Turk and techniques like distant supervision that aut...
Bayesian Modeling and MCMC Computation in Linear Logistic Regression for Presence-only Data
Bayesian modeling case-control design data augmentation logistic regres-sion Markov Chain Monte Carlo population prevalence presence-only data simulation
2013/6/13
Presence-only data are referred to situations in which, given a censoring mechanism, a binary response can be observed only with respect to on outcome, usually called \textit{presence}. In this work w...
Adaptivity of averaged stochastic gradient descent to local strong convexity for logistic regression
Adaptivity averaged stochastic gradient descent local strong convexity logistic regression
2013/4/28
In this paper, we consider supervised learning problems such as logistic regression and study the stochastic gradient method with averaging, in the usual stochastic approximation setting where observa...
K-Nearest Neighbour algorithm coupled with logistic regression in medical case-based reasoning systems. Application to prediction of access to the renal transplant waiting list in Brittany
Case-based Reasoning systems logistic models similarity measures k-nearest neighbors algorithms classi-fication
2013/4/28
Introduction. Case Based Reasoning (CBR) is an emerg- ing decision making paradigm in medical research where new cases are solved relying on previously solved similar cases. Usually, a database of sol...
Ordinal Logistic Regression for the Estimate of the Response Functions in the Conjoint Analysis
Aggregate Level Analysis Conjoint Analysis Ordinal Logistic Regression Response Function
2013/2/23
In the Conjoint Analysis (COA) model proposed here – a new approach to estimate more than one response function–an extension of the traditional COA, the polytomous response variable (i.e. evaluation o...
Matrix Variate Logistic Regression Analysis
Asymptotic theory Logistic regression Matrix variate covariates Regularization Tensor object
2011/6/17
Logistic regression has been widely applied in the field of biostatistics for a long
time. It aims to model the conditional success probability of an event of interest
as the logit function of a lin...
Using Logistic Regression to Analyze the Balance of a Game: The Case of StarCraft II
Balance of a Game Logistic Regression StarCraft II
2011/6/16
Recently, the market size of online game has been increasing astonishingly fast, and so does the
importance of good game design. In online games, usually a human user competes with others,
so the fa...
High-dimensional Ising model selection using ${\ell_1}$-regularized logistic regression
High-dimensional model selection
2010/10/14
We consider the problem of estimating the graph associated with a binary Ising Markov random field. We describe a method based on $\ell_1$-regularized logistic regression, in which the neighborhood of...
Honest variable selection in linear and logistic regression models via $ell_1$ and $ell_1 + ell_2$ penalization
penalty sparse consistent variable selection regression generalized linear models logistic regression
2009/9/16
This paper investigates correct variable selection in finite samples via $ell_1$ and $ell_1 + ell_2$ type penalization schemes. The asymptotic consistency of variable selection immediately follows fro...
Comparing two samples by penalized logistic regression
Empirical likelihood biased sampling penalty semiparametric shrinkage mean square error power
2009/9/16
Inference based on the penalized density ratio model is proposed and studied. The model under consideration is specified by assuming that the log--likelihood function of two unknown densities is of so...
Sensitivity Analysis to Select the Most Influential Risk Factors in a Logistic Regression Model
Risk Factors Logistic Regression Model
2009/9/3
The traditional variable selection methods for survival data depend on iteration procedures, and control of this process assumes tuning parameters that are problematic and time consuming, especially i...