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Proactive Data Mining with Decision Trees

demonstrate how applying the proactive approach to classification tasks can solve business problems. Proactive Data Mining with Decision Trees;

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Data Mining with Decision Trees

Decision trees have become one of the most powerful and popular approaches in knowledge discovery and data mining; it is the science;

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Data Mining With Decision Trees

This is the first comprehensive book dedicated entirely to the field of decision trees in data mining and covers all aspects of this;

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Decision Trees for Business Intelligence and Data Mining

This example-driven guide illustrates the application and operation of decision trees in data mining, business intelligence, business;

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Data Mining with Microsoft SQL Server 2008

Understand how to use the new features of Microsoft SQL Server 2008 for data mining by using the tools in Data Mining with Microsoft SQL;

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DATA MINING and MACHINE LEARNING. CLASSIFICATION PREDICTIVE TECHNIQUES: SUPPORT VECTOR MACHINE, LOGISTIC REGRESSION, DISCRIMINANT ANALYSIS and DECISION TREES

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Stream Data Mining: Algorithms and Their Probabilistic Properties

This book presents a unique approach to stream data mining. Unlike the vast majority of previous approaches, which are largely based on;

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Decision and Inhibitory Trees and Rules for Decision Tables with Many-valued Decisions

of data mining, knowledge discovery, and machine learning, especially those whose work involves decision tables with many-valued decisions. The;

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Decision and Inhibitory Trees and Rules for Decision Tables with Many-valued Decisions

of data mining, knowledge discovery, and machine learning, especially those whose work involves decision tables with many-valued decisions. The;

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Design and Implementation of a Model to Predict the Success of the Bank Telemarketing

Decision Tree is a successful data mining technique for predicting bank telemarketing success. The Decision Tree is a well known classifier and;

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Better Decision Tree from Intelligent Instance Selection

This book describes theoretical and experimental studies of instance selection to improve data mining model. Data preparation is one of the;

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Lecture Notes In Data Mining

of data mining techniques by explaining some of the basics such as applications of Bayes Theorem, similarity measures, and decision trees. Before;

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Ensemble decision trees

, which solves two of typical data mining problems observed in financial data mining field: the problem of imbalanced data and the problem;

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Foundations of Computational Intelligence 06

Mining problems. Computational tools or solutions based on intel- gent systems are being used with great success in Data Mining applications. It;

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Data Mining Techniques 3rd

common business problems * Covers a new data mining technique in every chapter along with clear, concise explanations on how to apply each;

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Comparative Analysis of Deterministic and Nondeterministic Decision Trees

of decision trees, including bounds on complexity and algorithms for construction of decision trees for decision tables with many-valued decisions. It;

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Comparative Analysis of Deterministic and Nondeterministic Decision Trees

study of decision trees, including bounds on complexity and algorithms for construction of decision trees for decision tables with many-valued;

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Data Mining and Decision Support

Data mining deals with finding patterns in data that are by user-definition, interesting and valid. It is an interdisciplinary area;

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Mining of Massive Datasets

popularity of the Web and Internet commerce provides many extremely large datasets from which information can be gleaned by data mining. This book;

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Data Mining and Statistics for Decision Making

statistics, machine learning and information theory; it is the ideal tool for such an extraction of knowledge. Data mining is usually associated with;

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Data Mining Methods

which readers can build various data mining modelson their owniC* Extensive reference section at the end of each chapter, with 300+ research;

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Data Mining Algorithms

Researchers and Professionals in data mining and related fields should be familiar with different models and standard algorithms in use to;

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Aerial Threat Perception Using Data Mining

. In this framework data mining and pattern classification techniques are incorporated. This paper focuses on effective prediction by relying on the;

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Clinical Data Mining for Physician Decision Making and Investigating Health Outcomes

Clinical Data Mining for Physician Decision Making and Investigating Health Outcomes: Methods for Prediction and Analysis demonstrates how;

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Big Data, Mining, and Analytics

, Mining, and Analytics: Components of Strategic Decision Making ties together big data, data mining, and analytics to explain how readers can;

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Big Data, Mining, and Analytics

, Mining, and Analytics: Components of Strategic Decision Making ties together big data, data mining, and analytics to explain how readers can;

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Domain Driven Data Mining

Data mining has emerged as one of the most active areas in information and c- munication technologies(ICT). With the boomingof the global;

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