... 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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... 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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... 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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... 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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... 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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... 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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... 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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... 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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... 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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... 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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... 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** 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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... 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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... 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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... 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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... 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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... 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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... 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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... 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** 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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