Logistic Regression
How To Use Logistic Regression On A Palm Handheld
... of logistic regression models on handheld ...with logistic regression models, the concept that we have described in this paper is general and can be extended to other modeling ...
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Logistic regression analysis on the determinants of stillbirth in Ethiopia
... level logistic regression were used. In the single level logistic regression model, region of residence, maternal age, place of residence, education level, parity, antenatal care utilization, ...
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A Comparison of Classification/Regression Trees and Logistic Regression in Failure Models
... One of the most relevant models specifically made for SMEswas developed by (Altman, & Sabato, 2007). Their study compares the traditional Z-score model with two new models which consider other financial variables and ...
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Trauma scoring models using logistic regression.
... Hosmer et al (1997) performed the first systematic simulation study of goodness of fit tests used in logistic regression. These authors studied the performance of the HL test in its different formats i.e. ...
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Logistic Regression on Homomorphic Encrypted Data at Scale
... for logistic regression on homomorphic encrypted data, and demonstrate its practical feasibility against realis- tic size data, for the first time to the best of our ...
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An Improved GLMNET for L1-regularized Logistic Regression
... In Section 3, we show that for expensive loss functions, Newton-type methods are more suit- able. A Newton method needs not compute the loss function when finding the Newton direction, which is the most time consuming ...
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On goodness-of-fit of logistic regression model
... The current goodness-of-fit tests can be roughly categorized into four types. (1) The tests are based on covariate patterns, e.g., Pearson’s Chi-square test, Deviance D test, and Osius and Rojek’s normal approximation ...
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Churn Analysis in Telecommunication Using Logistic Regression
... customers. Logistic Regression is been used to make necessary ...with logistic regression we must first eliminate the outliers that are present, this has be achieved by cleaning the data (for ...
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Transfer learning based on logistic regression
... a logistic re- gression classifier using the training samples from the source do- main (source domain samples) using the method described in sec- tion ...on logistic regression on the current ...
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An Application on Multinomial Logistic Regression Model
... OLS regression, however, logistic regression does not assume linearity of relationship between the independent variables and the dependent, does not require normally distributed variables, does not ...
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Purposeful selection of variables in logistic regression
... The purposeful selection process begins by a univariate analysis of each variable. Any variable having a significant univariate test at some arbitrary level is selected as a can- didate for the multivariate analysis. We ...
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Ordinal logistic regression in epidemiological studies
... Ordinal logistic regression models have shown to be suitable for analyzing data with ordinal response. The choice of the best model depends on the character of the ordinal variable, adaptation of the model ...
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Logistic regression applied to natural hazards: rare event logistic regression with replications
... ordinary logistic regression strongly underestimates the probability of occurrence of rare ...the logistic regression technique, so-called “rare event logistic regression”, that ...
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Characterization of Differentially Private Logistic Regression
... The purpose of this paper is to present an approach that can help data owners select suitable values for the privacy parameter of a differentially private logistic regression (DPLR), whose main intention is ...
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Sparse Logistic Regression with Logical Features
... in regression models poses both com- putational as well as statistical challenges: the computational resources and the amount of data required to solve them increases sharply with the size of the ...on ...
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Detection of Internet Scam Using Logistic Regression
... We propose to reduce the omissions and biases in blacklists by integrating information from various heterogeneous sources, particularly focusing on the quantitative measurements that are hard to manipulate, such as the ...
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Robust Logistic Regression using Shift Parameters
... standard logistic regression when anno- tation errors are ...of logistic regression shows particular promise for NLP applications: it helps account for incorrect labels, while remaining ...
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Deforestation modelling using logistic regression and GIS
... and logistic regression analyses were employed to predict the spatial distribution of deforestation and detects factors influencing forest degradation of Hyrcanian forests of western Gilan, ...The ...
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Bayesian Multinomial Logistic Regression for Author Identification
... In this paper we focus on multinomial or polytomous generalizations of logistic regression. An important advantage of this approach is that it outputs an estimate of the probability that an object ...
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Logistic regression analysis in personal loan bankruptcy
... Logistic regression is a type of generalized linear model that uses statistical analysis to predict an event based on known ...a logistic model and logit ...ordinary regression as well as ...
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