incorporating majority voting and involving Multilayer Perceptron (MLP), Logistic Regression (LR), decision trees (J48), Random …

This thesis is a study of the detection of separation among the sample points in binary logistic regression models. We … routinely as part of the fitting process for logistic regression models.The parameter estimates of a binary logistic regression … simulation study shows that this test can be computed in a similar amount of time as fitting the binary logistic regression model …

nongenetic factors. For rare diseases, the case-control study is a practical design, and logistic regression is the standard … logistic regression does not make use of this assumption and consequently is not statistically efficient. In recent work to … association parameters is conveniently obtained by fitting a conditional logistic regression. The statistical properties of the …

In this paper, we propose a novel method for sparse logistic regression with non-convex regularization Lp (p <1). Based … logistic regression with an Lp and elastic net (Le) penalty. The regularization parameters are decided through maximizing the … the literature. Our computational results show that Lp Logistic regression (p <1) outperforms the L1 logistic regression …

A logistic regression model is developed within the framework of a Geographic Information System (GIS) to map landslide … topography were analyzed by logistic regression analysis, and the results are used for landslide hazard mapping. In this study … geologic and geomorphic conditions is also analyzed, and used to develop a logistic regression model for landslide hazard …