The paper presents an approach to the task of automatic document categorization in the field of economics. Since the documents can be annotated with multiple keywords (labels), we ...
Narrative-centered learning environments introduce novel opportunities for supporting student problem solving and learning. By incorporating cognitive tools into plots and characte...
Background: Multiclass classification of microarray data samples with a reduced number of genes is a rich and challenging problem in Bioinformatics research. The problem gets hard...
Elizabeth Tapia, Leonardo Ornella, Pilar Bulacio, ...
We present some greedy learning algorithms for building sparse nonlinear regression and classification models from observational data using Mercer kernels. Our objective is to dev...
Prasanth B. Nair, Arindam Choudhury 0002, Andy J. ...
Software defect prediction strives to improve software quality and testing efficiency by constructing predictive classification models from code attributes to enable a timely ident...
Stefan Lessmann, Bart Baesens, Christophe Mues, Sw...
We investigate the performance of different classification models and their ability to recognize prostate cancer in an early state. We build ensembles of classification models in ...
1 In this paper we characterize and model the cost of rework in a Component Factory (CF) organization. A CF is responsible for developing and packaging reusable software components...
Victor R. Basili, Steven E. Condon, Khaled El Emam...
The standard framework of machine learning problems assumes that the available data is independent and identically distributed (i.i.d.). However, in some applications such as image...