High quality information on forest resources is important to forest ecosystem management.
Traditional ground measurements are labor and resource intensive and at the same time …

Methods for learning decision rules are being successfully applied to many problem
domains, in particular when understanding and interpretation of the learned model is …

Multi-target regression is concerned with the simultaneous prediction of multiple continuous
target variables based on the same set of input variables. It arises in several interesting …

The motive for this study was to learn to predict forest fires in Slovenia using different data
mining techniques. We used predictive models based on the forest structure GIS …

The predictive performance of traditional supervised methods heavily depends on the
amount of labeled data. However, obtaining labels is a difficult process in many real-life …

We address the task of multi-target regression, where we generate global models that
simultaneously predict multiple continuous variables. We use ensembles of generalized …

A constant and controlled level of emission of carbon and other gases into the atmosphere is
a pre-condition for preventing global warming and an essential issue for a sustainable …

We present CLUSplus, a machine learning framework based on decision trees specialized
for complex predictive modeling tasks. We provide the scientific community with an open …

Prediction of agricultural yields is a challenging task that demands fusion of knowledge from
different areas such as data mining, statistics and agriculture. This paper shows that data …

Methods for learning decision rules are being successfully applied to many problem
domains, especially where understanding and interpretation of the learned model is …