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Searching for authors named "Carlos Soares" – sorted by Relevance.

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  • Zoomed Ranking: Selection of Classification Algorithms Based on Relevant Performance Information  
  • by Carlos Soares And, Carlos Soares, Pavel B. Brazdil — 2000 — In Proceedings of Principles of Data Mining and Knowledge Discovery, 4th European Conference (PKDD-2000
  • …. Given the wide variety of available classification algorithms and the volume of data today's organizations need to analyze, the selection of the right algorithm to use on a new problem is an important issue. In this paper we present a combination of techniques to address this problem. The firs…
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  • On the Use of Fast Subsampling Estimates for Algorithm Recommendation  
  • by Johannes Fürnkranz, Johann Petrak, Pavel Brazdil, Carlos Soares — 2002 — Österreichisches Forschungsinstitut für Artificial Intelligence
  • …The use of subsampling for scaling up the performance of learning algorithms has become fairly popular in the recent literature. In this paper, we investigate the use of performance estimates obtained on a subsample of the data for the task of recommending the best learning algorithm(s) for the p…
  • Cited by 5 (0 self) – Add To MetaCart
  • A Comparison of Ranking Methods for Classification Algorithm Selection  
  • by Pavel B. Brazdil, Carlos Soares — 2000 — In Proceedings of the European Conference on Machine Learning ECML2000 (to Be Published
  • …. We investigate the problem of using past performance information to select an algorithm for a given classification problem. We present three ranking methods for that purpose: average ranks, success rate ratios and significant wins. We also analyze the problem of evaluating and comparing these …
  • Cited by 13 (6 self) – Add To MetaCart
  • Report on the Experiments with Feature Selection in Meta-Level Learning  
  • by Ljupco Todorovski, Pavel Brazdil, Carlos Soares — 2000 — Proceedings of the PKDD-00 Workshop on Data Mining, Decision Support, Meta-Learning and ILP: Forum for Practical Problem Presentation and Prospective Solutions
  • …The task of meta-level learning is to relate the performance of dierent machine learning algorithms on a given data set to some measurable characteristics of that data set. That can help the choice of suitable machine learning algorithm for a given data set. In dierent meta-level studies a vast n…
  • Cited by 1 (0 self) – Add To MetaCart
  • Ranking Classification Algorithms with Dataset Selection: Using Accuracy and Time Results  
  • by Carlos Soares, Pavel B. Brazdil — In Michalski, R., & Brazdil, P. (Eds.), Proceedings of the 5 th International Workshop on Multistrategy Learning
  • …. Given that wide variety of available classification algorithms exists, the selection of the right algorithm to use on a new problem is an important issue. In this paper we present zooming, that analyzes a given dataset and selects relevant (similar) datasets used in the past. This process is b…
  • Cited by 1 (0 self) – Add To MetaCart
  • Outlier Detection Using Clustering Methods: a Data Cleaning Application  
  • by Antonio Loureiro, Luis Torgo, Carlos Soares — 2004 — IN PROCEEDINGS OF THE DATA MINING FOR BUSINESS WORKSHOP
  • …This paper describes a methodology for the application of hierarchical clustering methods to the task of outlier detection. The methodology is tested on the problem of cleaning Official Statistics data. The goal…
  • Cited by 2 (0 self) – Add To MetaCart
  • Using Meta-Learning to Support Data Mining  
  • by Ricardo Vilalta, Christophe Giraud-carrier, Pavel Brazdil, Carlos Soares
  • …Current data mining tools are characterized by a plethora of algorithms but a lack of guidelines to select the right method according to the nature of the problem under analysis. Producing such guidelines is a primary goal by the field of meta-learning; the research objective is to understand the in…
  • Cited by 1 (0 self) – Add To MetaCart
  • Ranking Classification Algorithms Based on Relevant Performance Information  
  • by Pavel B. Brazdil, Carlos Soares — 2000 — MetaLearning: Building Automatic Advice Strategies for Model Selection and Method Combination, 2000
  • …. Given the wide variety of available classification algorithms and the volume of data today's organizations need to analyze, the selection of the right algorithm to use on a new problem is an important issue. In this paper we present zooming, a technique that, for a given dataset, selects relev…
  • Cited by 3 (1 self) – Add To MetaCart
  • Dynamic Discretization of Continuous Attributes  
  • by João Gama, Luis Torgo, Carlos Soares — 1998 — In Proceedings of the Sixth Ibero-American Conference on AI
  • …Discretization of continuous attributes is an important task for certain types of machine learning algorithms. Bayesian approaches, for instance, require assumptions about data distributions. Decision Trees, on the other hand, require sorting operations to deal with continuous attributes, which …
  • Cited by 2 (0 self) – Add To MetaCart
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