J. R. Statist. Soc. B[removed], Part 4, pp. 815–849 Clustering objects on subsets of attributes Jerome H. Friedman Stanford University, USA

Source URL: www.math.mtu.edu

• Data mining
• Geostatistics
• Hierarchical clustering
• Feature selection
• Statistics
• Cluster analysis
• Data analysis

DOCUMENTARY FORTNIGHT 2014 BRINGS AN INTERNATIONAL SELECTION OF NEW FILMS TO THE MUSEUM OF MODERN ART IN FEBRUARY Festival Includes 20 Feature Films, 10 Shorts, and Two Classics from 20 Countries Documentary Fortnight 20

Source URL: press.moma.org

Elder, J. F. IV[removed]Proceedings of 26th Symposium on the Interface, Research Triangle Park, NC, June 15-18, pp[removed]Growing Decision Trees Less Greedily John F. Elder IV, Rice University* Dept. Computational & A

Source URL: datamininglab.com

• Computational statistics
• Model selection
• Decision trees
• Decision tree learning
• Feature selection
• Stepwise regression
• Data mining
• Greedy algorithm
• Artificial neural network
• Statistics
• Machine learning
• Regression analysis

Object class recognition and localization using sparse features with limited receptive fields ∗ Jim Mutch † Department of Brain and Cognitive Sciences Massachusetts Institute of Technology Cambridge, MA

Source URL: www.mit.edu

• Statistics
• Image processing
• California Institute of Technology
• Caltech 101
• Object recognition
• Feature selection
• Support vector machine
• Template matching
• Filter
• Computer vision
• Vision
• Imaging

Flashes in a Star Stream: Automated Classification of Astronomical Transient Events

Source URL: www.kiss.caltech.edu

• Statistical classification
• Machine learning
• Naive Bayes classifier
• Data analysis
• Bayesian network
• Transient astronomical event
• Gravitational microlensing
• Feature selection
• Regression analysis
• Statistics
• Astronomy
• Bayesian statistics

Feature Selection Bias in Classification of High Dimensional Data John H Maindonald December 5, 2013 Abstract This vignette reproduces modified versions the calculations and the

Source URL: cran.r-project.org

• Multivariate statistics
• Statistical classification
• Linear discriminant analysis
• Cross-validation
• Algebraic number theory
• Validation
• Feature selection
• Discriminant
• Statistics
• Machine learning
• Model selection

Adverse Selection and the Required Return Nicolae Gaˆrleanu University of Pennsylvania Lasse Heje Pedersen New York University An important feature of financial markets is that securities are traded repeatedly by

Source URL: faculty.haas.berkeley.edu

• Finance
• Stock market
• Financial risk
• Bid–offer spread
• Market maker
• Order
• Futures contract
• Market liquidity
• Dark liquidity
• Financial markets
• Financial economics
• Investment

Identifying Genes with The Concept of Customization Dong Hua George Washington University Washington, DC[removed]removed]

Source URL: www.seas.gwu.edu

• Genetics
• Genomics
• Dimension reduction
• Gene
• Ridge
• Feature selection
• Minimum redundancy feature selection
• Biology
• Molecular biology
• Gene expression

Evaluating Feature Selection Methods for Multi-Label Text Classification Newton Spolaôr1, Grigorios Tsoumakas2 1 Laboratory of Computational Intelligence,

Source URL: bioasq.org

• Hindu population in England & Wales
• Hinduism in the United Kingdom
• Perceptron

Integrating Randomization and Discrimination for Classifying Human-Object Interaction Activities Aditya Khosla, Bangpeng Yao and Li Fei-Fei 1 Introduction

Source URL: people.csail.mit.edu

• Statistical classification
• Decision trees
• Ensemble learning
• Computer vision
• Random forest
• Feature selection
• Object recognition
• Decision tree learning
• Segmentation
• Statistics
• Machine learning
• Artificial intelligence