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Decision tree learning
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#	Item
81	Neural Decision Forests for Semantic Image Labelling Samuel Rota Bul`o Fondazione Bruno Kessler Trento, Italy Peter Kontschieder Add to Reading List Source URL: www.dsi.unive.it Language: English - Date: 2014-04-15 04:23:50 Perceptron Multilayer perceptron Maximum likelihood Artificial neuron Random forest Activation function Decision tree learning Backpropagation Artificial neural network Neural networks Machine learning Statistics
82	Multi-Interval Discretization Methods for Decision Tree Learning Add to Reading List Source URL: www.data-mining-tutorial.de Language: English - Date: 2009-10-09 07:20:51 Artificial intelligence Numerical analysis Machine learning C4.5 algorithm Learning Vector Quantization Decision tree learning Discretization Vector quantization Mathematics Decision trees Computational statistics
83	Texture Classification based on the Boolean Model and its Application to Hep-2 Cells Add to Reading List Source URL: www.data-mining-tutorial.de Language: English - Date: 2009-10-09 07:21:17 Artificial intelligence Learning Decision tree learning Boolean model Statistical classification Decision tree model Random forest Machine learning Decision trees Computational statistics
84	476 IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. 19, NO. 5, MAY 1997 A Comparative Analysis of Methods for Pruning Decision Trees Add to Reading List Source URL: aass.oru.se Language: English - Date: 2005-03-31 13:13:25 Pruning Grafting Tree Decision tree learning T-tree Random forest Collision detection Decision trees Graph theory Mathematics
85	Classification of HEp-2 Cells using Fluorescent Image Analysis and Data Mining Add to Reading List Source URL: www.data-mining-tutorial.de Language: English - Date: 2009-10-09 07:21:20 Statistical classification Pattern recognition Feature extraction Linear discriminant analysis Feature Data mining Decision tree learning Boosting methods for object categorization Book:Machine Learning - The Complete Guide Statistics Machine learning Artificial intelligence
86	USING DATA MINING TO PREDICT SECONDARY SCHOOL STUDENT PERFORMANCE Paulo Cortez and Alice Silva Dep. Information Systems/Algoritmi R&D Centre University of MinhoGuimar˜aes, PORTUGAL Add to Reading List Source URL: www3.dsi.uminho.pt Language: English - Date: 2008-08-01 07:17:42 Statistical classification Decision trees Support vector machine Feature selection Regression analysis Data mining Cross-validation Decision tree learning Data analysis Statistics Machine learning Model selection
87	Decision Tree Learning read Chapter 3] recommended exercises 3.1, 3.4] Decision tree representation ID3 learning algorithm Entropy, Information gain Add to Reading List Source URL: aass.oru.se Language: English - Date: 2005-03-31 12:57:41 Cybernetics Statistical theory Science Applied mathematics Philosophy of thermal and statistical physics Information theory Entropy Decision tree learning Kullback–Leibler divergence Statistics Thermodynamic entropy Decision trees
88	Variable selection using Random Forests Robin Genuer, Jean-Michel Poggi, Christine Tuleau-Malot To cite this version: Robin Genuer, Jean-Michel Poggi, Christine Tuleau-Malot. Variable selection using Random Forests. Patt Add to Reading List Source URL: hal.archives-ouvertes.fr Language: English - Date: 2015-02-02 11:22:56 Decision trees Statistical models Ensemble learning Random forest Dummy variable Linear regression Variance Decision tree learning Quantification Statistics Regression analysis Econometrics
89	Journal of Artificial Intelligence Research883 Submitted 06/13; publishedScalable and Efficient Bayes-Adaptive Reinforcement Learning Based on Monte-Carlo Tree Search Add to Reading List Source URL: www.gatsby.ucl.ac.uk Language: English - Date: 2013-11-28 14:07:54 Markov models Dynamic programming Markov processes Stochastic control Reinforcement learning Markov decision process Monte Carlo method Markov chain Monte Carlo Graphical model Statistics Probability and statistics Bayesian statistics
90	An Extension of the CHAID Tree-based Segmentation Algorithm to Multiple Dependent Variables Jay Magidson1 and Jeroen K. Vermunt2 1 2 Add to Reading List Source URL: statisticalinnovations.com Language: English - Date: 2009-01-30 12:07:07 Econometrics Categorical data Psychometrics CHAID Latent class model Multinomial logit Decision tree learning Latent variable Factor analysis Statistics Regression analysis Decision trees

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