Data mining for business analytics: concepts, techniques, and applications in R

Data mining for business analytics: concepts, techniques, and applications in R

Overview of the data mining process -- Data visualization -- Dimension reduction -- Evaluating predictive performance -- Multiple linear regression -- k-Nearest Neighbors (kNN) -- The Naive Bayes classifier -- Classification and regression trees -- Logistic regression -- Neural nets -- Discriminant...

Ausführliche Beschreibung

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Bibliographische Detailangaben
Hauptverfasser: Shmueli, Galit, Bruce, Peter C, Yahav, Inbal, Patel, Nitin R, Lichtendahl, Kenneth C., Jr
Format: Buch
Sprache:eng
Schlagworte:
Business
Business mathematics
Computer programs
Data mining
Data processing
Erfolgsfaktor
Performance-Messung
R (Computer program language)
Unternehmensanalyse
Wissenschaftliche Methode
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Beschreibung
Zusammenfassung:Overview of the data mining process -- Data visualization -- Dimension reduction -- Evaluating predictive performance -- Multiple linear regression -- k-Nearest Neighbors (kNN) -- The Naive Bayes classifier -- Classification and regression trees -- Logistic regression -- Neural nets -- Discriminant analysis -- Combining methods : ensembles and uplift modeling -- Association rules and collaborative filtering -- Cluster analysis -- Handling time series -- Regression-based forecasting -- Smoothing methods -- Social network analytics -- Text mining -- Cases