This paper compares, for a microfinance institution, the performance of two individual classification models: Logistic Regression (Logit) and Multi-Layer Perceptron Neural Network (MLP), to evaluate the credit risk problem and discriminate good creditors from bad ones. Credit scoring systems are currently in common use by numerous financial institutions worldwide. However, credit scoring using ...

The use of non-parametric methodologies, the introduction of non-financial variables, and the development of models geared towards the homogeneous characteristics of corporate sub-populations have recently experienced a surge of interest in the bankruptcy literature. However, no research on default prediction has yet focused on micro-entities (MEs), despite such firms’ importance in the global ...

closed-loop supply chain network (clscn) design aims at incorporating environmental considerations into the traditional supply chain design by including recycling, disassembly and reuse activities. in a clscn, the environmental considerations can also be facilitated by resorting to environmentally friendly materials and enhancing product reuse through the design of an appropriate product recove...

background one of the main objects in medical science is diagnosis the diseases and classification the patients to different classes. consequently according to the above the patients that set in one classes should have maximum similarity with each other. discrimination and classification analysis have been frequently used in medical data for diagnosis and prognostic of the disease. the wrong in...

Nowadays one of the most important challenges for integrated systems such as social networks is the evaluation of trust for agents which are interacting with each other in the environment. It plays an important role that the trust has been evaluated from the agent’s experiences. In this paper, we propose a new mathematical approach based on the entropy of Dirichlet distribution, to model the ag...

We propose a new method for learning the parameters of a Bayesian network with qualitative influences. The proposed method aims to remove unwanted (context-specific) independencies that are created by the order-constrained maximum likelihood (OCML) estimator. This is achieved by averaging the OCML estimator with the fitted probabilities of a first-order logistic regression model. We show experi...

Diffusion of innovations and knowledge is in most cases accounted for by the logistic model. Fieldwork research however constantly report that empirical data utterly deviate from this mathematical function. This chapter scrutinizes network forcing of diffusion process. The departure of empirical data from the logistic function is explained by social network discreteness, heterogeneity and aniso...

This paper proposes the use of Bayesian Causal Maps (BCM s) to analyze the complex structure of inflation in Turkey. In this study, a model of inflation is initially structured using a cognitive mapping technique; the dependent probabilities of the concepts are then calculated based on the detailed analysis of past data. Finally, a BCM is used to analyze the complex structure of inflation in Tu...