Data Mining and Knowledge Discovery Handbook
Binding: Hardcover
Rating: 4.0
Review: 2
Studio: Springer
This handbook organizes all major concepts, theories, methodologies, trends, challenges and applications of data mining (DM) and knowledge discovery in databases (KDD) into a coherent and unified whole. The book first surveys, then provides comprehensive yet concise algorithmic descriptions of classic methods plus recently-developed extensions and novel methods. The volume concludes with in-depth descriptions of data mining applications in various interdisciplinary industries including finance, marketing, medicine, biology, engineering, telecommunications, software, and security. Data Mining and Knowledge Discovery Handbook is designed for research scientists and graduate-level computer science and engineering students. It is also suitable for professionals in fields such as computing applications, information systems management, and strategic research management.
Manufacturer: Springer
Price: $269.00 USD
Data Mining : an Overview
Artificial neural networks: Non-linear predictive models that learn through training and resemble biological neural networks in structure. Decision trees: Tree-shaped structures that represent sets of decisions. These decisions generate
Machine Learning
Binding: Hardcover
Rating: 4.5
Review: 36
Studio: McGraw-Hill Science/Engineering/Math
This book covers the field of machine learning, which is the study of algorithms that allow computer programs to automatically improve through experience. The book is intended to support upper level undergraduate and introductory level graduate courses in machine learning.
Manufacturer: McGraw-Hill Science/Engineering/Math
Artificial Intelligence Methods in the Environmental Sciences
Binding: Paperback
Rating: 4.5
Review: 36
Studio: Springer
How can environmental scientists and engineers use the increasing amount of available data to enhance our understanding of planet Earth, its systems and processes? This book describes various potential approaches based on artificial intelligence (AI) techniques, including neural networks, decision trees, genetic algorithms and fuzzy logic. Part I contains a series of tutorials describing the methods and the important considerations in applying them. In Part II, many practical examples illustrate the power of these techniques on actual environmental problems. International experts bring to life ways to apply AI to problems in the environmental sciences. While one culture entwines ideas with a thread, another links them with a red line. Thus, a red thread ties the book together, weaving a tapestry that pictures the natural data-driven AI methods in the light of the more traditional modeling techniques, and demonstrating the power of these data-based methods.
Manufacturer: Springer
Price: $89.95 USD
Data Mining Tools, Understanding Data Mining
important factors to consider when selecting a data mining tool include the platforms supported, algorithms on which they work (neural networks, decisions trees), input and output options for data, database structure and storage required,
Artificial Intelligence
) about objects based on their attributes (length, colour…). Given a series of examples, the learning algorithm can build a decision tree that will be able of classifying new examples. If the new examples are handled correctly, nothing is
Agriculture Crop Management and Production Improved by Satellite Remote Sensing Technology and Geographic Information Systems (gis)
of Agriculture Management developing TreeGrading Maps to reveal the location and extent of each tree canopy determined by using a proprietary spectral algorithm. The properties of the GVI satellite images within each polygon are extracted
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