Predictive analytics and data mining concepts and practice with RapidMiner
This book shows how to analyze data, uncover hidden patterns and relationships to aid important decisions and predictions. Topics include: exploratory data analysis; visualization; decision trees; rule induction; k-nearest neighbors; naive Bayesian; artificial neural networks; support vector machine...
| Main Authors: | , |
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| Format: | eBook |
| Language: | English |
| Published: |
Waltham, MA
Morgan Kaufmann
2015
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| Online Access: | |
| Collection: | O'Reilly - Collection details see MPG.ReNa |
| Summary: | This book shows how to analyze data, uncover hidden patterns and relationships to aid important decisions and predictions. Topics include: exploratory data analysis; visualization; decision trees; rule induction; k-nearest neighbors; naive Bayesian; artificial neural networks; support vector machines; ensemble models; bagging; boosting; random forests; linear regression; logistic regression; association analysis using Apriori and FP growth; k-means clustering; density based clustering; self organizing maps; text mining; time series forecasting; anomaly detection and feature selection. -- |
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| Physical Description: | 1 online resource 1 volume illustrations |
| ISBN: | 0128014601 0128016507 9780128016503 |