While there is extensive literature on the prediction of corporate bankruptcies, little classification retail borrowers. This also true in Hungary. Recognising who at risk becoming a bad debtor not easy. There are several ways to analyse data, which may yield different results. In this paper, my aim predict default household loans using logistic regression and neural networks. The question is, ...

Problem statement: This study discusses the implementation of advanced logistic belief Neural Network for robot arms control. Approach: Given the desired trajectory of the end-effectors in space, the logistic function is used to compute the conditional probability of the neurons being active in response to its induced field. The computations of conditional probabilities are performed under two ...

An important challenge in machine learning is to find ways of learning quickly from very small amounts of training data. The only way to learn from small data samples is to constrain the learning process by exploiting background knowledge. In this report, we present a theoretical analysis on the use of constrained logistic regression for estimating conditional probability distribution in Bayesi...