LUIS TORGO PDF
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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Luís Torgo – Google Scholar Citations
Please check the confirmation e-mail of your application to obtain the access code. The book follows a “learn by doing it” approach to data mining instead of the more frequent theoretical description of the techniques available in this discipline.
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I am the author of the widely acclaimed Data Mining with R book published by CRC Press in with a strongly revised second edition that appeared in Otrgo subscription has been successfully removed. PMLR94, pp. The book writing style establishes it as a good source for practical classes on data mining, but also as an attractive document to professionals working on data mining in non-academic environments.
Encyclopedia of Machine Learning Inductive learning to tree-based regression models. Verified email at dal. Spatial Interpolation Using Multiple Regression.
Clustered Partial Linear Regression. Arbitrated Ensemble for Time Series Forecasting.
Recent Publications More Publications. Wind speed forecasting using spatio-temporal indicators. Predicting Rare Extreme Values.
It is not politically correct, nor does it intend to be the voice of the Board of Directors. The system can’t perform the operation now. Portuguese conference on artificial intelligence, Design of an end-to-end method to extract information from tables. Title Cited by Year Data mining with R: Data Mining with R: European Working Session on Learning, Data mining with R: 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.
Detecting Errors in Foreign Trade Transactions: Arbitrage of Forecasting Experts Expert Systems 35 4 Joaquin VanschorenJan N. Walter Van de Velde. An open, collaborative, frictionless, automated machine learning environment. Data Mining I CC Aquatic Microbial Ecology80 2pp. 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. Data Mining Machine Learning. Regression Using Classification Algorithms.
Abstract Social media are becoming an increasingly important source of information about the public mood regarding issues such as elections, Brexit, stock market, etc.
One full year in a row as 1 selling Data Mining book at amazon. Luis Torgo main contributions to the state of the art on data mining and machine learning are related with tree-based regression methods and more recently with utility-based forecasting methods.
Adapting Peepholing to Regression Otrgo. His current broad research interests revolve around analyzing data from dynamic environments, with a particular focus on time and space-time dependent data sets, in the search for unexpected events.
Ensembles for Time Series Forecasting.