Decision Tree Analysis : Data Mining with Decision Trees Theroy and Applications Machine Perception and Artificial Intelligence

Six Sigma Data Analysis
forecasts, overlay, trend and sensitivity), as well as select some or all of your assumption, forecast and decision variable cells from your spreadsheet. You can change the display from a Tree view to a List view.User Macros : The macro
Audience Response Systems - Interactive Powerpoint Presentation
and Events, surveys and research, sales, marketing, polling and voting, Decision makings.I would also like to share research made by Decision Tree Consulting (DTC) over a period of time for Audience Response System. You must be
Classification trees A possible method for maternity risk grouping An article from European Journal of Operational Research
Binding: Digital
Rating: 3.0
Review: 1
Studio: Elsevier
This digital document is a journal article from European Journal of Operational Research, published by Elsevier in . The article is delivered in HTML format and is available in your Amazon.com Media Library immediately after purchase. You can view it with any web browser.Description: Pregnancy, although being one of the most natural processes in our evolution, still remains subject to numerous complications and potential high risk. Complications at birth, such as the need for a caesarean section or the use of forceps, are not uncommon. An early warning of possible complications would greatly benefit both medical professionals and the expectant mother. Classification tree analysis uses selected independent variables to group pregnant women according to a dependent variable in a way that reduces variation. In this study, data on 3902 births were analysed to create risk groups for a number of complications, including the risk of a non-spontaneous delivery (a complicated birth) and premature delivery. From an overall risk of 23% of a non-spontaneous delivery, the classification tree was able to find statistically significant risk groups ranging from 7% to 65%. The resulting classification rules have been incorporated into a developed database tool to help quantify associated risks and act as an early warning system of possible complications to individual pregnant women.
Manufacturer: Elsevier
Price: $5.95 USD
Data Mining with Decision Trees Theroy and Applications Machine Perception and Artificial Intelligence
Binding: Hardcover
Rating: 3.0
Review: 1
Studio: World Scientific Publishing Company
This is the first comprehensive book dedicated entirely to the field of decision trees in data mining and covers all aspects of this important technique. Decision trees have become one of the most powerful and popular approaches in knowledge discovery and data mining, the science and technology of exploring large and complex bodies of data in order to discover useful patterns. The area is of great importance because it enables modeling and knowledge extraction from the abundance of data available. Both theoreticians and practitioners are continually seeking techniques to make the process more efficient, cost-effective and accurate. Decision trees, originally implemented in decision theory and statistics, are highly effective tools in other areas such as data mining, text mining, information extraction, machine learning, and pattern recognition.This book invites readers to explore the many benefits in data mining that decision trees offer: self-explanatory and easy to follow when compacted; able to handle a variety of input data: nominal, numeric and textual; able to process datasets that may have errors or missing values; high predictive performance for a relatively small computational effort; available in many data mining packages over a variety of platforms; and, useful for various tasks, such as classification, regression, clustering and feature selection.
Manufacturer: World Scientific Publishing Company
Price: $87.00 USD
Data Analysis Services
our Data Analysis consultants are also available discuss your analysis options with you and help you to understand the types of decisions that can be made from the data you want to collect. The results will be quickly made available to you
The Music of Middle Earth - an Analysis on the Use of Music in the Film: "the Lord of the Rings: the Fellowship of the Ring"
string section. The music is heroic and we feel the importance of their quest. We are excited and proud of them for making the decision to destroy the Ring and save Middle Earth. Later, the Fellowship takes refuge in the Mines of
How To Avoid Paralysis By Analysis
to focus on who the few are and copy them? Ok we know your mind just pivoted over into Analysis mode again, didn t it? You re saying, How can I possibly find out who the few are? Where on earth would I find that information, let alone
A change detection model based on neighborhood correlation image analysis and decision tree classification An article from Remote Sensing of Environment
Binding: Digital
Rating: 3.0
Review: 1
Studio: Elsevier
This digital document is a journal article from Remote Sensing of Environment, published by Elsevier in . The article is delivered in HTML format and is available in your Amazon.com Media Library immediately after purchase. You can view it with any web browser.Description: This study introduces a change detection model based on Neighborhood Correlation Image (NCI) logic. It is based on the fact that the same geographic area (e.g., a 3x3 pixel window) on two dates of imagery will tend to be highly correlated if little change has occurred, and uncorrelated when change occurs. Computing the piecewise correlation between two data sets provides valuable information regarding the location and numeric change value derived using contextual information within the specified neighborhood. Various neighborhood configurations (i.e., multi-level NCIs) were explored in the study using high spatial resolution multispectral imagery: smaller neighborhood sizes provided some detailed change information (such as a new patios added to an existing building) at the cost of introducing some noise (such as changes in shadows). Larger neighborhood sizes were useful for removing this noise but introduced some inaccurate change information (such as removing some linear feature changes). When combined with image classification using a machine learning decision tree (C5.0), classifications based on multi-level NCIs yielded superior results (e.g., using a 3-pixel circular radius neighborhood had a Kappa of 0.94), compared to the classification that did not incorporate NCIs (Kappa=0.86).
Manufacturer: Elsevier
Price: $8.95 USD

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