Eibe Frank

Searching and Evaluating . . . . . . . . . . . . . . . . . . . . . . . . . 10 Options . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 Performing Selection . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 ... The scatter plot matrix . . . . . . . . . . . . . . . . . . . . . . . . . . 11 Selectin an individual 2D scatter plot . . . . . . . . . . . . . . . . . . ...

Association rule mining is a data mining technique that reveals interesting relationships in a database. Existing approaches employ different parameters to search for interesting rules. This fact and the large number of rules make it difficult to compare the output of confidence ...

ABSTRACT Inducing classifiers that make accurate predictions on future data is a driving force for research in inductive learning. However, also of importance to the users is how to gain information from the models produced. Unfortunately, some of the most powerful inductive learning algorithms generate “black boxes”—that is, the representation of the model makes it virtually impossible to gain any insight into what has been learned. This paper presents a technique that can help the user understand why a classifier makes the predictions that it does by providing a two-dimensional visualization of its class probability estimates. It requires the classifier to generate class probabilities but most practical algorithms are able to do so (or can be modified to this end).

ABSTRACT The much-publicized Netflix competition has put the spotlight on the application domain of collaborative filtering and has sparked interest in machine learning algorithms that can be applied to this sort of problem. The demanding nature of the Netflix data has lead to some interesting and ingenious modifications to standard learning methods in the name of efficiency and speed. There are three basic methods that have been applied in most approaches to the Netflix problem so far: stand-alone neighborhood-based methods, latent factor models based on singular-value decomposition, and ensembles consisting of variations of these techniques. In this paper we investigate the application of forward stage-wise additive modeling to the Netflix problem, using two regression schemes as base learners: ensembles of weighted simple linear regressors and k-means clustering—the latter being interpreted as a tool for multi-variate regression in this context. Experimental results show that our methods produce competitive results.

The hypothesis was that sensors currently available on farm that monitor behavioral and physiological characteristics have potential for the detection of lameness in dairy cows. This was tested by applying additive logistic regression to variables derived from sensor data. Data were collected between November 2010 and June 2012 on 5 commercial pasture-based dairy farms. Sensor data from weigh scales (liveweight), pedometers (activity), and milk meters (milking order, unadjusted and adjusted milk yield in the first 2 min of milking, total milk yield, and milking duration) were collected at every milking from 4,904 cows. Lameness events were recorded by farmers who were trained in detecting lameness before the study commenced. A total of 318 lameness events affecting 292 cows were available for statistical analyses. For each lameness event, the lame cow's sensor data for a time period of 14 d before observation date were randomly matched by farm and date to 10 healthy cows (i.e., ...

Inflammatory bowel diseases (IBD) are emerging globally, indicating that environmental factors may be important in their pathogenesis. Colonic mucosal epigenetic changes, such as DNA methylation, can occur in response to the environment and have been implicated in IBD pathology. However, mucosal DNA methylation has not been examined in treatment-naïve patients. We studied DNA methylation in untreated, left sided colonic biopsy specimens using the Infinium HumanMethylation450 BeadChip array. We analyzed 22 control (C) patients, 15 untreated Crohn's disease (CD) patients, and 9 untreated ulcerative colitis (UC) patients from two cohorts. Samples obtained at the time of clinical remission from two of the treatment-naïve UC patients were also included into the analysis. UC-specific gene expression was interrogated in a subset of adjacent samples (5 C and 5 UC) using the Affymetrix GeneChip PrimeView Human Gene Expression Arrays. Only treatment-naïve UC separated from control. One-hundred-and-twenty genes with significant expression change in UC (> 2-fold, P<0.05) were associated with differentially methylated regions (DMRs). Epigenetically associated gene expression changes (including gene expression changes in the IFITM1, ITGB2, S100A9, SLPI, SAA1, and STAT3 genes) were linked to colonic mucosal immune and defense responses. These findings underscore the relationship between epigenetic changes and inflammation in pediatric treatment-naïve UC and may have potential etiologic, diagnostic, and therapeutic relevance for IBD.

More than twelve years have elapsed since the first public release of WEKA. In that time, the software has been re- written entirely from scratch, evolved substantially and now accompanies a text on data mining (35). These days, WEKA enjoys widespread acceptance in both academia and busi- ness, has an active community, and has been downloaded more than 1.4 million

Logistic Model Trees have been shown to be very accurate and compact classifiers [8]. Their greatest disadvantage is the computational complexity of inducing the logistic regression models in the tree. We address this issue by using the AIC criterion [1] instead of cross-...

This paper shows how Wikipedia and the semantic knowledge it contains can be exploited for document clustering. We first create a concept-based document representation by mapping the terms and phrases within documents to their corresponding articles (or concepts) in Wikipedia. We also developed a similarity measure that evaluates the semantic relatedness between concept sets for two documents. We test the concept-based representation and the similarity measure on two standard text document datasets. Empirical results show that although further optimizations could be performed, our approach already improves upon related techniques. This is an author’s accepted version of an article published in Proceedings of 13th Pacific-Asia Conference, PAKDD 2009 Bangkok, Thailand, April 27-29. ©2009 Springer-Verlag Berlin Heidelberg.

The Weka workbench is an organized collection of state-of-the-art machine lear-ning algorithms and data preprocessing tools. The basic way of interacting with these methods is by invoking them from the command line. However, convenient interactive graphical user ...