This research explores machine learning methods for the development of computer models that use gene expression data to distinguish between tumor and non-tumor, between metastatic and non-metastatic, and between histological subtypes of lung cancer. A second goal is to identify small sets of gene predictors and study their properties in terms of stability, size, and relation to lung cancer. We ...

HLearn is a Haskell-based library for machine learning. Its distinguishing feature is that it exploits the algebraic properties of learning models. Every model in the library is an instance of the HomTrainer type class, which ensures that the batch trainer is a monoid homomorphism. This is a restrictive condition that not all learning models satisfy; however, it is useful for two reasons. First...

We compare the performance of several automatic classification systems across a collection of different feature sets in detecting the gender of Japanese authors. The Japanese language is notable for the distinctiveness of the different manners and modes of speech used by the two genders--speakers of one gender often use different verb forms, sentence-final particles, and even personal pronouns ...

Motivation: PSORTb v.1.1 is the most precise bacterial localization prediction tool available. However the program’s predictive coverage and recall are low and the method is only applicable to Gram-negative bacteria. The goals of the present work were: increase PSORTb’s coverage while maintaining the existing precision level, expand it to include Gram-positive bacteria, and then carry out a com...

English. In this paper we describe our approach to EVALITA 2016 SENTIPOLC task. We participated in all the subtasks with constrained setting: Subjectivity Classification, Polarity Classification and Irony Detection. We developed a tandem architecture where Long Short Term Memory recurrent neural network is used to learn the feature space and to capture temporal dependencies, while the Support V...

During last decade, needs for high resolution land cover data have been growing. Such knowledge is namely often required in environment monitoring studies. Thus, to answer these needs, national mapping or environment agencies, in many countries, have undertaken the production of such large scale national land cover database. Nevertheless, these databases provide a general classification and may...

We consider the problem of image recognition in social media websites. Social-media website's users have been doing image recognition task unconsciously all the time, such as, tagging images or looking at images. We would like to utilize this valuable human's effort. Thus, we propose a preliminary image recognition system trained using images scraped from the internet, and an iOS application th...

In the TREC 2008, the team from the State University of New York at Buffalo participated in the Legal track and the Blog track. For the Legal track, we worked on the interactive search task using the Web-based Legacy Tobacco Document Library Boolean search system. Our experiment achieved reasonable precision but suffered significantly from low recall. These results, together with the appealing ...