Tuesday, January 31, 2017

Random Forest (3) - Varian

Artikel ini merupakan kelanjutan dari artikel sebelumnya tentang Random Forest.

 Variasi Random Forest

Variasi Random Forest
Variasi Random Forest


Terdapat banyak turunan atau variasi dari Algoritma Random Forest (RF). Beberapa diantaranya adalah: 
  • Deep Neural Decision Forests [Paper]

    • Peter Kontschieder, Madalina Fiterau, Antonio Criminisi, and Samuel Rota Bulo, Deep Neural Decision Forests, ICCV 2015
  • Canonical Correlation Forests [Paper]

    • Tom Rainforth, and Frank Wood, Canonical Correlation Forests, arxiv 2015
  • Relating Cascaded Random Forests to Deep Convolutional Neural Networks [Paper]

    • David L Richmond, Dagmar Kainmueller, Michael Y Yang, Eugene W Myers, and Carsten Rother, Relating Cascaded Random Forests to Deep Convolutional Neural Networks for Semantic Segmentation, arxiv 2015
  • Bayesian Forests [Paper]

    • Taddy Matthew, Chun-Sheng Chen, Jun Yu, Mitch Wyle, Bayesian and Empirical Bayesian Forests, ICML 2015
  • Mondrian Forests: Efficient Online Random Forests [Paper] [Code] [Slides]

    • Balaji Lakshminarayanan, Daniel M. Roy and Yee Whye Teh, Mondrian Forests: Efficient Online Random Forests, NIPS 2014
  • Extremely randomized trees P Geurts, D Ernst, L Wehenkel - Machine learning, 2006 [Paper] [Code]

  • Decision Jungles [Paper]

    • Jamie Shotton, Toby Sharp, Pushmeet Kohli, Sebastian Nowozin, John Winn, and Antonio Criminisi, Decision Jungles: Compact and Rich Models for Classification, NIPS 2013
    • Laptev, Dmitry, and Joachim M. Buhmann. Transformation-invariant convolutional jungles. CVPR 2015. [Paper]
  • Semi-supervised Node Splitting for Random Forest Construction [Paper]

    • Xiao Liu, Mingli Song, Dacheng Tao, Zicheng Liu, Luming Zhang, Chun Chen and Jiajun Bu, Semi-supervised Node Splitting for Random Forest Construction, CVPR 2013
  • Improved Information Gain Estimates for Decision Tree Induction [Paper]

    • Sebastian Nowozin, Improved Information Gain Estimates for Decision Tree Induction, ICML 2012
  • MIForests: Multiple-Instance Learning with Randomized Trees [Paper] [Code]

    • Christian Leistner, Amir Saffari, and Horst Bischof, MIForests: Multiple-Instance Learning with Randomized Trees, ECCV 2010
  • Alternating Decision Forests.

    • Samuel Schulter, Paul Wohlhart, Christian Leistner, Amir Saffari, Peter M. Roth, Horst Bischof,CVPR 2013 Paper
  • Decision Forests, Convolutional Networks and the Models in-Between [Paper]

  • Random Uniform Forests Saïp Ciss [Paper] [Code R]

  • Autoencoder Trees, Ozan İrsoy, Ethem Alpaydın 2015 [Paper

 

Semoga bermanfaat dan tunggu artikel mengenai Decision Forest berikutnya.

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Random Forest (3) - Varian
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