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Ali Abbasi
Ali Abbasi
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DATA MINING AND MACHINE LEARNING IN A NUTSHELL ACTIVE LEARNING Mohammad-Ali Abbasi http://www.public.asu.edu/~mabbasi2/ SCHOOL OF COMPUTING, INFORMATICS, AND DECISION SYSTEMS ENGINEERING ARIZONA STATE UNIVERSITY Arizona State University http://dmml.asu.edu/ Data Mining and Machine Learning Lab Data Mining and Machine Learning- in a nutshell Active Learning 1
What is Active Learning The process of guiding the sampling process by querying for certain types of instances based upon the data that we have seen so far Arizona State University Data Mining and Machine Learning Lab Data Mining and Machine Learning- in a nutshell Active Learning 2
The importance of Active learning • The process of labeling the training data is not only time-consuming but also very expensive • Less training data we need, more we will save Arizona State University Data Mining and Machine Learning Lab Data Mining and Machine Learning- in a nutshell Active Learning 3
Applications • Text classification • Web page classification • Junk mail recognition Arizona State University Data Mining and Machine Learning Lab Data Mining and Machine Learning- in a nutshell Active Learning 4
Methods • Neural Networks • Bayesian rule • SVM No matter which method will be used, the core problem will be the same •The core problem is how to select training points actively? •In other words, which training points will be informative to the model? Arizona State University Data Mining and Machine Learning Lab Data Mining and Machine Learning- in a nutshell Active Learning 5
Active vs. Passive Learning • Passive: – Randomly select training samples • Active – Use an automated method to select training samples Arizona State University Data Mining and Machine Learning Lab Data Mining and Machine Learning- in a nutshell Active Learning 6
References • Theory, Methods and Applications of Active Learning – Robert Nowak, Department of Electrical and Computer Engineering, University of Wisconsin - Madison – Rui Castro, Department of Electrical Engineering, Columbia University – Published: July 30, 2009, recorded: June 2009 – http://videolectures.net/mlss09us_nowak_castro_tmaal/ Arizona State University Data Mining and Machine Learning Lab Data Mining and Machine Learning- in a nutshell Active Learning 7
Mohammad-Ali Abbasi (Ali), Ali, is a Ph.D student at Data Mining and Machine Learning Lab, Arizona State University. His research interests include Data Mining, Machine Learning, Social Computing, and Social Media Behavior Analysis. http://www.public.asu.edu/~mabbasi2/ Arizona State University Data Mining and Machine Learning Lab Data Mining and Machine Learning- in a nutshell Active Learning 8

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Active learning

  • 1. DATA MINING AND MACHINE LEARNING IN A NUTSHELL ACTIVE LEARNING Mohammad-Ali Abbasi http://www.public.asu.edu/~mabbasi2/ SCHOOL OF COMPUTING, INFORMATICS, AND DECISION SYSTEMS ENGINEERING ARIZONA STATE UNIVERSITY Arizona State University http://dmml.asu.edu/ Data Mining and Machine Learning Lab Data Mining and Machine Learning- in a nutshell Active Learning 1
  • 2. What is Active Learning The process of guiding the sampling process by querying for certain types of instances based upon the data that we have seen so far Arizona State University Data Mining and Machine Learning Lab Data Mining and Machine Learning- in a nutshell Active Learning 2
  • 3. The importance of Active learning • The process of labeling the training data is not only time-consuming but also very expensive • Less training data we need, more we will save Arizona State University Data Mining and Machine Learning Lab Data Mining and Machine Learning- in a nutshell Active Learning 3
  • 4. Applications • Text classification • Web page classification • Junk mail recognition Arizona State University Data Mining and Machine Learning Lab Data Mining and Machine Learning- in a nutshell Active Learning 4
  • 5. Methods • Neural Networks • Bayesian rule • SVM No matter which method will be used, the core problem will be the same •The core problem is how to select training points actively? •In other words, which training points will be informative to the model? Arizona State University Data Mining and Machine Learning Lab Data Mining and Machine Learning- in a nutshell Active Learning 5
  • 6. Active vs. Passive Learning • Passive: – Randomly select training samples • Active – Use an automated method to select training samples Arizona State University Data Mining and Machine Learning Lab Data Mining and Machine Learning- in a nutshell Active Learning 6
  • 7. References • Theory, Methods and Applications of Active Learning – Robert Nowak, Department of Electrical and Computer Engineering, University of Wisconsin - Madison – Rui Castro, Department of Electrical Engineering, Columbia University – Published: July 30, 2009, recorded: June 2009 – http://videolectures.net/mlss09us_nowak_castro_tmaal/ Arizona State University Data Mining and Machine Learning Lab Data Mining and Machine Learning- in a nutshell Active Learning 7
  • 8. Mohammad-Ali Abbasi (Ali), Ali, is a Ph.D student at Data Mining and Machine Learning Lab, Arizona State University. His research interests include Data Mining, Machine Learning, Social Computing, and Social Media Behavior Analysis. http://www.public.asu.edu/~mabbasi2/ Arizona State University Data Mining and Machine Learning Lab Data Mining and Machine Learning- in a nutshell Active Learning 8