This paper addresses the fundamental problem of document classification, and we focus attention on classification problems where the classes are mutually exclusive. In the course of the paper we advocate an approximate sampling distribution for word counts in documents, and demonstrate the model’s capacity to outperform both the simple multinomial and more recently proposed extensions on the cl...

Longitudinal network data recording the moment at which ties appear, change, or disappear are increasingly available. Event history models can be used to analyze the dynamics of time-stamped network data. This paper adapts the discrete-time event history model to social network data. A discrete-time event history model can easily incorporate a multilevel design and time-varying covariates. A mu...

We present a new approach to training back-propagation artificial neural nets (BP-ANN) based on regularization and cross-validation and on initialization by a logistic regression (LR) model. The new approach is expected to produce a BP-ANN predictor at least as good as the LR-based one. We have applied the approach to ten data sets of biomedical interest and systematically compared BP-ANN and L...

Logistic regression is the standard method for developing prognostic models for intensive care, but this approach does not take into account the uncertainty in the model selected and the uncertainty in its regression coefficients. This weakness can be addressed by adopting a Bayesian model-averaged approach to logistic regression; however, with respect to the dataset used for our study, we foun...

Booking cancellation is a key aspect of hotel revenue management as it affects the room reservation system. has significant effect on which impact demand decisions in industry. In order to reduce effect, applies model addressing this problem with machine learning-based system developed. study, using data collection from Kaggle website name hotel-booking-demand dataset. The research objective wa...

results overall, the prevalence of unwanted pregnancies was 32.3%. the performance of the models based on the area under the roc curve as the indicator was as follows: artificial neural networks (0.741), decision tree (0.731), and logistic regression (0.712). the highest sensitivity level belonged to the decision tree (73.5%), and the highest specificity level belonged to the artificial neural ...