SYLVA is an ecology dataset

The task of SYLVA is to classify forest cover types. The forest cover type for 30 x 30 meter cells is obtained from US Forest Service (USFS) Region 2 Resource Information System (RIS) data. We brought it back to a two-class classification problem (classifying Ponderosa pine vs. everything else). The data consists in 216 input variables. Each pattern is composed of 4 records: 2 true records matching the target and 2 records picked at random. Thus ½ of the features are distracters. The SYLVA dataset was used previously in the Performance Prediction challenge, the Model Selection game, and the Agnostic Learning vs. Prior Knowledge (ALvsPK) challenge.