Probabilistic modelling of wildfire occurrence based on logistic regression, Niassa Reserve, Mozambique

Multinomial Logistic Regression on Markov Chains for Crop Rotation Modelling

Often, in dynamical systems, such as farmer’s crop choices, the dynamics is driven by external nonstationary factors, such as rainfall, temperature, and economy. Such dynamics can be modelled by a nonstationary Markov chain, where the transition probabilities are logistic functions of such external factors. We investigate the problem of estimating the parameters of the logistic model from data,...

Merging Strategy Based on Logistic Regression

With the development of network technology, the users looking for information may send a request to various selected databases and then inspect multiple result lists. To overcome such multiple inspections, the database merging strategy involves the merging of the retrieval results produced by separate, autonomous servers into an effective, single ranked list. To achieve this merging, this study...

Transfer Learning Based on Logistic Regression

In this paper we address the problem of classification of remote sensing images in the framework of transfer learning with a focus on domain adaptation. The main novel contribution is a method for transductive transfer learning in remote sensing on the basis of logistic regression. Logistic regression is a discriminative probabilistic classifier of low computational complexity, which can deal w...

Predicting shrimp disease occurrence: artificial neural networks vs. logistic regression

Predicting the occurrence of disease outbreaks in aquacultural farms can be of considerable value to the long-term sustainable development of the industry. Prior research on disease prediction has essentially depended upon traditional statistical models with varying degrees of prediction accuracy. Furthermore, the application of these models in sustainable aquaculture development and in control...

Notes on Logistic Regression