Proceedings of KDNet Symposium on Knowledge-based systems for the Public Sector, , Functional models for regression tree leaves. L Torgo. List of computer science publications by Luís Torgo. Luis Torgo is an Associate Professor of the Department of Computer Science of the Faculty of Sciences of the University of Porto, Portugal. He is a senior.
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New articles related to this author’s research. This book is about learning how to use R for performing data mining.
Expert Systems 34 1 The results of this study contribute to the understanding of the dissimilatory nitrate-reducing pathways and help uncover their involvement in degradation of PAHs, which will be crucial for directing remediation strategies of PAH-contaminated anoxic sediments. My profile My library Metrics Alerts. Chemosphere, pp. He has been involved in many research projects under different roles and involving different types of organizations.
Rita Ribeiro Utility-based Regression. However, we observe that all cross-validation variants tend to overestimate the performance, while the sequential methods tend to underestimate it. This “Cited by” count includes citations to the following articles in Scholar. Socially Driven News Recommendation. Proceedings of Discovery Science Encyclopedia torbo Machine Learning Verified email at dal.
Resampling with neighbourhood bias on imbalanced domains. Construction of sentiment classifiers is a standard text mining task, but here we address the question of how to properly evaluate them as there is no settled way to do so.
Luis Torgo – CRC Press Online
Predictive Analytics and the Ocean Please check the confirmation e-mail of your application to obtain the access code. Applications to Financial Trading. Data Mining with R.
Potential of dissimilatory nitrate reduction pathways in polycyclic aromatic hydrocarbon degradation. Destructive sampling at the beginning and after 3, 6, 12, 30 and 63 weeks incubation was performed. In this work, we propose variants of existing resampling strategies that are able to take into account the information regarding the neighbourhood of the examples. Your subscription has been successfully removed. New articles by this author. Power and Energy Systems.
If you choose to, you can easily unsubscribe from the newsletter by following the link presented in the footer. Naphthalene and fluoranthene levels decreased over time with distinct degradation dynamics varying with sediment type. If you need to update your contact information or clarify any questions related to the newsletter, please send an email to scom inesctec.
Data Yorgo Machine Learning. OpenML An open, collaborative, frictionless, automated machine learning environment. This problem has been extensively studied for classification problems, where the target variable is nominal. A strongly revised and tkrgo Second Edition is out – check it!
Luis Torgo Home Page
Current Trends in Knowledge Acquisition, PMLR94, pp. Arbitrated Ensemble for Time Series Forecasting. He has a strong experience of teaching different subjects at different academic levels but also in togo settings. We created sentiment models and out-of-sample datasets, which are used as a gold standard for evaluations.
A comparative study of approaches to forecast the correct trading actions. Portuguese conference on artificial intelligence, Regression by classification L Torgo, J Gama Brazilian symposium on artificial intelligence, Kuis Regression Remove your e-mail address form our mailing list.
R academic applied-research basic-research biology concluded consulting-projects cost-sensitive learning costs ensembles evaluation feature engineering imbalance distributions imbalanced distributions imbalanced domains metal learning ongoing ongoing-projects past-projects phd postdoc regression trees relational learning spatiotemporal text mining time series utility utility’based learning.
Abstract This study investigates the potential of an indigenous estuarine microbial consortium to degrade two polycyclic aromatic hydrocarbons PAHsnaphthalene and fluoranthene, under nitrate-reducing conditions.