Exploració per autor "Bifet Figuerol, Albert Carles"

Ara es mostren els items 8-15 de 15

    • Data stream classification using random feature functions and novel method combinations 

      Marrón Vida, Diego; Read, Jesse; Bifet Figuerol, Albert Carles; Navarro, Nacho (2017-05-01)
      Article
      Accés obert
      Big Data streams are being generated in a faster, bigger, and more commonplace. In this scenario, Hoeffding Trees are an established method for classification. Several extensions exist, including high performing ensemble ...

    • Detecting sentiment change in twitter streaming data 

      Bifet Figuerol, Albert Carles; Holmes, Geoffrey; Pfahringer, Bernhard; Gavaldà Mestre, Ricard (2011)
      Text en actes de congrés
      Accés obert
      MOA-TweetReader is a real-time system to read tweets in real time, to detect changes, and to fi nd the terms whose frequency changed. Twitter is a micro-blogging service built to discover what is happening at any moment ...

    • Echo state hoeffding tree learning 

      Marrón Vida, Diego; Read, Jesse; Bifet Figuerol, Albert Carles; Abdessalem, Talel; Ayguadé Parra, Eduard; Herrero Zaragoza, José Ramón (Microtome Publishing, 2016)
      Text en actes de congrés
      Accés restringit per política de l'editorial
      Nowadays, real-time classi cation of Big Data streams is becoming essential in a variety of application domains. While decision trees are powerful and easy{to{deploy approaches for accurate and fast learning from data ...

    • Low-latency multi-threaded ensemble learning for dynamic big data streams 

      Marron, Diego; Ayguadé Parra, Eduard; Herrero Zaragoza, José Ramón; Read, Jesse; Bifet Figuerol, Albert Carles (Institute of Electrical and Electronics Engineers (IEEE), 2018)
      Text en actes de congrés
      Accés obert
      Real–time mining of evolving data streams involves new challenges when targeting today’s application domains such as the Internet of the Things: increasing volume, velocity and volatility requires data to be processed ...

    • Mining frequent closed graphs on evolving data streams. 

      Bifet Figuerol, Albert Carles; Holmes, Geoff; Pfahringer, Bernhard; Gavaldà Mestre, Ricard (ACM Press, NY, 2011)
      Text en actes de congrés
      Accés restringit per política de l'editorial
      Graph mining is a challenging task by itself, and even more so when processing data streams which evolve in real-time. Data stream mining faces hard constraints regarding time and space for processing, and also needs to ...

    • Mining frequent closed rooted trees 

      Balcázar Navarro, José Luis; Bifet Figuerol, Albert Carles; Lozano Boixadors, Antoni (2010-01)
      Article
      Accés obert
      Many knowledge representation mechanisms are based on tree-like structures, thus symbolizing the fact that certain pieces of information are related in one sense or another. There exists a well-studied process of closure-based ...

    • New ensemble methods for evolving data streams 

      Bifet Figuerol, Albert Carles; Holmes, Geoffrey; Pfahringer, Bernhard; Kirkby, R; Gavaldà Mestre, Ricard (Association for Computing Machinery (ACM), 2009)
      Text en actes de congrés
      Accés restringit per política de l'editorial
      Advanced analysis of data streams is quickly becoming a key area of data mining research as the number of applications demanding such processing increases. Online mining when such data streams evolve over time, that is ...

    • teex: a toolbox for the evaluation of explanations 

      Antoñanzas Acero, Jesús Maria; Jia, Yunzhe; Frank, Eibe; Bifet Figuerol, Albert Carles; Pfahringer, Bernhard (Elsevier, 2023-10-28)
      Article
      Accés obert
      We present teex, a Python toolbox for the evaluation of explanations. teex focuses on the evaluation of local explanations of the predictions of machine learning models by comparing them to ground-truth explanations. It ...