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Logistic Regression
In many problems in science and practice, the following questions arise: Which one of two or more alternative states is present or which event will...
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Logistic Regression
Linear regression modeling is well suited to predicting continuous data where the outcome y is a real number (i.e., y ∈ ℝ). Logistic regression is a...
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Logistic Regression and Discriminant Analysis
Questions like whether a customer is going to buy a product (purchase vs. non-purchase) or whether a borrower is creditworthy (pay off debt vs....
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Estimating labor commuting patterns using polytomous response logistic regression
A laborshed analysis examines the available workforce that flows from the surrounding communities into a nodal city. Iowa Workforce Development...
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Logistic Regression
In many problems in science and practice, the following questions arise: Which one of two or more alternative states is present or which event will...
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Segmenting fare-evaders by tandem clustering and logistic regression models
In this study, a tandem clustering is applied on data collected by an Italian public transport company. Three clusters of evader passengers are...
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Applications of Logistic Regression and Hazard Method in Accounting and Finance Research
This chapter introduces commonly used models to study whether or when an event occurs in accounting and finance research. I begin with parametric...
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Loss-optimal classification trees: a generalized framework and the logistic case
Classification trees are one of the most common models in interpretable machine learning. Although such models are usually built with greedy...
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Business success prediction in Rwanda: a comparison of tree-based models and logistic regression classifiers
Businesses contribute immensely to economic growth. However, many enterprises started fail within a year of their operation. This study seeks to...
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Logistische Regression
Bei vielen Problemstellungen in Wissenschaft und Praxis treten immer wieder die folgenden Fragen auf: Welcher von zwei oder mehreren alternativen...
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Shrinkage Estimation for Location and Scale Parameters of Logistic Distribution Under Record Values
Logistic distribution (LogDis) is frequently used in many different applications, such as logistic regression, logit models, classification, neural...
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Discrete half-logistic distributions with applications in reliability and risk analysis
In the statistical literature, several discrete distributions have been developed so far for modeling non-negative integer-valued phenomena, yet...
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Regression Analysis Using Dummy Variables
Regression analysis is a versatile method for the analysis and description of business problems. It is based on the development of a model that...
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Applications of Logistic Regression and Hazard Method in Accounting and Finance Research
This chapter introduces commonly used models to study whether or when an event occurs in accounting and finance research. I begin with parametric...
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Regression
Regression is the task of calculating a numerical value based on an object’s set of characteristics. One important sub-branch consists of methods...
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Linear Regression
Regression aims at predicting a future value, so the outcome we are trying to predict is a number, not a class. Many problems can be reduced to...
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Role of Engineering Technology on Logistic Performance in Promoting Economic Growth in Asian Countries
Engineering technology and logistic performance become key elements of sustainable long-run economic growth and have been explained in endogenous...
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Estimation of a logistic regression model by a genetic algorithm to predict pipe failures in sewer networks
Sewer networks are mainly composed of pipelines which are in charge of transporting sewage and rainwater to wastewater treatment plants. A failure in...
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Recovery process optimization using survival regression
The goal of this paper is to propose, empirically test and compare different logistic and survival analysis techniques in order to optimize the debt...
