Revision history for TutoriumMustererkennungEnsemblemethodenSS18
Additions:
----
CategoryTutorienFKITSS18
CategoryTutorienFKITSS18
No Differences
Additions:
**{{color text="Tutor:" c="#00386a"}}**
**{{color text="Ziel des Tutoriums:" c="#00386a"}}**
**{{color text="Adressaten des Lehrangebotes:" c="#00386a"}}**
**{{color text="Veranstaltungsinhalte:" c="#00386a"}}**
**{{color text="Literaturhinweise:" c="#00386a"}} **
**{{color text="Ziel des Tutoriums:" c="#00386a"}}**
**{{color text="Adressaten des Lehrangebotes:" c="#00386a"}}**
**{{color text="Veranstaltungsinhalte:" c="#00386a"}}**
**{{color text="Literaturhinweise:" c="#00386a"}} **
Deletions:
**{{color text="2. Ziel des Tutoriums:" c="#00386a"}}**
**{{color text="3. Adressaten des Lehrangebotes:" c="#00386a"}}**
**{{color text="4. Teilnahme:" c="#00386a"}}**
**{{color text="5. Veranstaltungsdatum/-zeit/-ort:" c="#00386a"}}**
**{{color text="6. Veranstaltungsinhalte:" c="#00386a"}}**
**{{color text="7. Literaturhinweise:" c="#00386a"}} **
Additions:
[[http://wiki.hs-schmalkalden.de/Ensemble_Vergleiche Vergleiche:]]
Deletions:
Additions:
- [[http://wiki.hs-schmalkalden.de/Random_Forest Random Forest]]
Deletions:
Additions:
- [[http://wiki.hs-schmalkalden.de/AdaBoost AdaBoost]]
Deletions:
Additions:
- [[http://wiki.hs-schmalkalden.de/GradientBoosting Gradient Boosting]]
Deletions:
Deletions:
Additions:
Interessenten aus dem Fachbereich Informatik
Deletions:
Additions:
[1] Breiman L. (1994): Bagging Predictors; University of California -Department of Statistics
[2] Freund Y., Schapire R. E. (1999): A Short Introduction to Boosting; AT & T Labs - Research
[3] Hastie T., Tibshirani R. and Friedman J. (2009): Elements of Statistical Learning - Data Mining, Inference, and Prediction; Springer
[4] Schapire R. E. (unbekannt): Explaining AdaBoost; Princeton University, Dept. of Computer Science
[5] Zhou, Zhi-Hua (2012): Ensemble Methods: Foundations and Algorithms; Taylor & Francis Ltd
[6] Zhu J., Zou H., Rosset S., Hastie T. (2006): Multi-class AdaBoost; 1085 South University
[2] Freund Y., Schapire R. E. (1999): A Short Introduction to Boosting; AT & T Labs - Research
[3] Hastie T., Tibshirani R. and Friedman J. (2009): Elements of Statistical Learning - Data Mining, Inference, and Prediction; Springer
[4] Schapire R. E. (unbekannt): Explaining AdaBoost; Princeton University, Dept. of Computer Science
[5] Zhou, Zhi-Hua (2012): Ensemble Methods: Foundations and Algorithms; Taylor & Francis Ltd
[6] Zhu J., Zou H., Rosset S., Hastie T. (2006): Multi-class AdaBoost; 1085 South University
Deletions:
[2] Hastie T., Tibshirani R. and Friedman J. (2009): Elements of Statistical Learning - Data Mining, Inference, and Prediction; Springer
[3] Schapire R. E. (unbekannt): Explaining AdaBoost; Princeton University, Dept. of Computer Science
[4] Zhou, Zhi-Hua (2012): Ensemble Methods: Foundations and Algorithms; Taylor & Francis Ltd
[5] Zhu J., Zou H., Rosset S., Hastie T. (2006): Multi-class AdaBoost; 1085 South University
Additions:
- AdaBoost
- Gradient Boosting
- Random Forest
- Gradient Boosting
- Random Forest
Deletions:
- "Gradient Boosting "
- "Random Forest"
Additions:
- "AdaBoost"
- "Gradient Boosting "
- "Random Forest"
- "Gradient Boosting "
- "Random Forest"
Deletions:
- Gradient Boosting
- Random Forest
Additions:
Vermittlung der Grundlagen der Ensemble-Methoden im automatischen rechnerbasierten Lernen
Fakultät Informatik ( ab Semester 4)
Vorstellung von:
- AdaBoost
- Gradient Boosting
- Random Forest
Vergleiche:
- Zwischen den Algorithmen
- Mit SVM und OLVQ
[1] Freund Y., Schapire R. E. (1999): A Short Introduction to Boosting; AT & T Labs - Research
[2] Hastie T., Tibshirani R. and Friedman J. (2009): Elements of Statistical Learning - Data Mining, Inference, and Prediction; Springer
[3] Schapire R. E. (unbekannt): Explaining AdaBoost; Princeton University, Dept. of Computer Science
[4] Zhou, Zhi-Hua (2012): Ensemble Methods: Foundations and Algorithms; Taylor & Francis Ltd
[5] Zhu J., Zou H., Rosset S., Hastie T. (2006): Multi-class AdaBoost; 1085 South University
Fakultät Informatik ( ab Semester 4)
Vorstellung von:
- AdaBoost
- Gradient Boosting
- Random Forest
Vergleiche:
- Zwischen den Algorithmen
- Mit SVM und OLVQ
[1] Freund Y., Schapire R. E. (1999): A Short Introduction to Boosting; AT & T Labs - Research
[2] Hastie T., Tibshirani R. and Friedman J. (2009): Elements of Statistical Learning - Data Mining, Inference, and Prediction; Springer
[3] Schapire R. E. (unbekannt): Explaining AdaBoost; Princeton University, Dept. of Computer Science
[4] Zhou, Zhi-Hua (2012): Ensemble Methods: Foundations and Algorithms; Taylor & Francis Ltd
[5] Zhu J., Zou H., Rosset S., Hastie T. (2006): Multi-class AdaBoost; 1085 South University
Deletions:
CategoryInfoTutorien
Additions:
----
CategoryInfoTutorien
CategoryInfoTutorien
