Decision Support Systems[removed] – 83 www.elsevier.com/locate/dsw Visualizing criminal relationships: comparison of a hyperbolic tree and a hierarchical list Yang Xianga,*, Michael Chaub, Homa Atabakhsha, Hsinchun

Source URL: www.business.hku.hk

• Infographics
• Knowledge representation
• Geometry
• Database management systems
• Data management
• Hyperbolic tree
• Visualization
• Database
• Tree
• Science
• Graph drawing
• Computer graphics

Community consultation – tree root pruning Generally tree root pruning requests by the community are considered by the City of Port Phillip for potential conflicts between infrastructure and tree roots and where potent

Source URL: m.portphillip.vic.gov.au

• Fruit tree pruning
• Decision trees
• Pruning
• Learning

Decision Tree on Wicket Approaches Eric Sawyer Last time we covered where to hit the first ball towards the next hoop. Placement of the first ball depended on which hoop we were shooting at, i.e., an odd numbered hoop,

Source URL: www.croquetamerica.com

• Ball games
• Olympic sports
• Sports
• Croquet
• Team sports

Salford Systems Critical Features of High performance Decision Trees Decision trees have justifiably become one of the most popular data mining tools. They are relatively easy to use, the results can usually be displayed

Source URL: media.salford-systems.com

• Artificial intelligence
• Decision tree learning
• Decision tree
• Pruning
• R-tree
• Data mining
• CHAID
• Decision trees
• Statistics
• Computational statistics

PLANET: Massively Parallel Learning of Tree Ensembles with MapReduce Biswanath Panda, Joshua S. Herbach, Sugato Basu, Roberto J. Bayardo Google, Inc. [bpanda, jsherbach, sugato]@google.com, [removed]

Source URL: static.googleusercontent.com

• Binary trees
• Machine learning
• Decision trees
• Distributed computing architecture
• MapReduce
• Parallel computing
• Decision tree learning
• Tree traversal
• B-tree
• Computing
• Concurrent computing
• Computer programming

Constanta Maritime University Annals Year XI, Vol.14 PREDICTION ANALYSIS OF BANKRUPTCY RISK USING BAYESIAN NETWORKS 1

Source URL: www.agena.co.uk

• Statistical models
• Statistical inference
• Networks
• Bayesian network
• Bayesian probability
• Decision tree
• Statistical power
• Statistical hypothesis testing
• Probability distribution
• Statistics
• Bayesian statistics
• Hypothesis testing

New Zealand Transport Agency “Answer Path is used by our Contact Centre Staff as a questionnaire/decision tree while attending customer phone calls. This software program is very easy to use; and has improved the compl

Source URL: www.answerpath.com

• Telephony
• Automation
• Marketing
• Call centre
• Contact centre
• New Zealand Transport Agency
• Customer support
• Business
• Systems engineering
• Customer experience management
• Technology
• Computer telephony integration

Chapter 9 lecture questions Q1: What are the conditions for the lowest ozone values to occur? Answer: In the decision tree below, the lowest ozone value of 5.61 ppm was attained by the leftmost leaf node, which satisfies

Source URL: www.ocgy.ubc.ca

Molecular Data Mining Tool: Advances In HIV Research he ability to predict biological activity based on molecular structure is leading researchers to breakthroughs in the most complex challenges of medicine. Using a

Source URL: media.salford-systems.com

• Econometrics
• Science
• Computational statistics
• Neural networks
• Artificial neural network
• Decision tree learning
• Multivariate adaptive regression splines
• Data mining
• Regression analysis
• Statistics
• Computational neuroscience
• Machine learning

1 CONCEPT FORMATION AND DECISION TREE INDUCTION USING THE GENETIC PROGRAMMING PARADIGM John R. Koza

Source URL: www.genetic-programming.com

• Computing
• Genetic algorithms
• Applied mathematics
• Genetic programming
• Operations research
• Lisp programming language
• Lisp
• John Koza
• Fitness function
• Evolutionary algorithms
• Software engineering
• Mathematical optimization