DATA MINING
Desktop Survival Guide
by
Graham Williams
Desktop Survival
Project Home
Preface
List of Figures
List of Tables
Process
.
Data
Graphics in R
Understanding Data
Preparing Data
Building Models
Evaluating Models
Algorithms
Apriori
Bagging
Bayes Classifier
Boosting
Conditional Trees
Decision Trees
Hierarchical Clustering
Kernel Methods
K-Means
K-Nearest Neighbours
Linear Models
Logistic Regression
Neural Networks
Support Vector Machines
Text Mining
Open Products
Borgelt Data Mining Suite
R
Rattle
Weka
Closed Products
C4.5
Clementine
Enterprise Miner
Equbits Foresight
GhostMiner
InductionEngine
ODM
Statistica Data Miner
TreeNet
Virtual Predict
Appendicies
Glossary
Bibliography
Index
Contents
Preface
List of Figures
List of Tables
Process
.
Data
Graphics in R
Understanding Data
Preparing Data
Building Models
Evaluating Models
Algorithms
Apriori: Association Analysis
Bagging: Meta Algorithm
Bayes Classifier: Classification
Boosting: Meta Algorithm
Bootstrapping: Meta Algorithm
Conditional Trees: Classification
Decision Trees: Classification
Hierarchical Clustering: Clustering
Kernel Methods: Classification
K-Means: Clustering
K-Nearest Neighbours: Classification
Linear Models
Logistic Regression: Regression
Neural Networks: Classification and Regression
Random Forests: Classification
Support Vector Machines: Classification
Text Mining
Open Products
Borgelt Data Mining Suite: From University of Magdeburg
R: From the R Foundation
Rattle: From Togaware
Weka: From University of Waikato
Closed Products
C4.5: Classification
Clementine: From SPSS
Enterprise Miner: From SAS
Equbits Foresight: Tool from Equbits
GhostMiner: From Fujitsu
InductionEngine: Tool from PredictionWorks
ODM: Tool from Oracle
Statistica Data Miner: From StatSoft
TreeNet: From Salford Systems
Virtual Predict: From Virtual Genetics
Appendicies
Glossary
Bibliography
Index
Copyright © 2004-2005
Brought to you by
Togaware
.