Predictive analytics and data mining : concepts and practice with rapidminer

Predictive analytics and data mining concepts and practice with rapidminer

Put Predictive Analytics into Action Learn the basics of Predictive Analysis and Data Mining through an easy to understand conceptual framework and immediately practice the concepts learned using the open source RapidMiner tool. Whether you are brand new to Data Mining or working on your tenth proj...

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Detalles Bibliográficos
Otros Autores: Kotu, Vijay, author (author), Deshpande, Bala, author
Formato: Libro electrónico
Idioma:Inglés
Publicado: Waltham, Massachusetts : Elsevier Inc 2015.
Edición:1st edition
Materias:
Data mining > Data processing.
Consumer behavior > Economic aspects.
Ver en Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009628613306719
Tabla de Contenidos:
  • ""Front Cover""; ""Predictive Analyticsand Data Mining""; ""Copyright""; ""Dedication""; ""Contents""; ""Foreword""; ""Preface""; ""WHY THIS BOOK?""; ""WHO CAN USE THIS BOOK?""; ""Acknowledgments""; ""Chapter 1 -Introduction""; ""1.1 WHAT DATA MINING IS""; ""1.2 WHAT DATA MINING IS NOT""; ""1.3 THE CASE FOR DATA MINING""; ""1.4 TYPES OF DATA MINING""; ""1.5 DATA MINING ALGORITHMS""; ""1.6 ROADMAP FOR UPCOMING CHAPTERS""; ""REFERENCES""; ""Chapter 2 - Data Mining Process""; ""2.1 PRIOR KNOWLEDGE""; ""2.2 DATA PREPARATION""; ""2.3 MODELING""; ""2.4 APPLICATION""; ""2.5 KNOWLEDGE""
  • ""REFERENCES""""Chapter 6 - Association Analysis""; ""6.1 CONCEPTS OF MINING ASSOCIATION RULES""; ""6.2 Apriori Algorithm""; ""6.3 FP-GROWTH ALGORITHM""; ""CONCLUSION""; ""REFERENCES""; ""Chapter 7 - Clustering""; ""CLUSTERING TO DESCRIBE THE DATA""; ""CLUSTERING FOR PREPROCESSING""; ""7.1 TYPES OF CLUSTERING TECHNIQUES""; ""7.2 K-MEANS CLUSTERING""; ""7.3 DBSCAN CLUSTERING""; ""7.4 SELF-ORGANIZING MAPS""; ""REFERENCES""; ""Chapter 8 - Model Evaluation""; ""8.1 CONFUSION MATRIX (OR TRUTH TABLE)""; ""8.2 RECEIVER OPERATOR CHARACTERISTIC (ROC) CURVES AND AREA UNDER THE CURVE (AUC)""
  • ""8.3 LIFT CURVES""""8.4 EVALUATING THE PREDICTIONS: IMPLEMENTATION""; ""CONCLUSION""; ""REFERENCES""; ""Chapter 9 - Text Mining""; ""9.1 HOW TEXT MINING WORKS""; ""9.2 IMPLEMENTING TEXT MINING WITH CLUSTERING AND CLASSIFICATION""; ""CONCLUSION""; ""REFERENCES""; ""Chapter 10 - Time Series Forecasting""; ""10.1 DATA-DRIVEN APPROACHES""; ""10.2 MODEL-DRIVEN FORECASTING METHODS""; ""CONCLUSION""; ""REFERENCES""; ""Chapter 11 - Anomaly Detection""; ""11.1 ANOMALY DETECTION CONCEPTS""; ""11.3 DENSITY-BASED OUTLIER DETECTION""; ""11.4 LOCAL OUTLIER FACTOR""; ""CONCLUSION""; ""REFERENCES""
  • ""Chapter 12 - Feature Selection""""12.1 CLASSIFYING FEATURE SELECTION METHODS""; ""12.2 PRINCIPAL COMPONENT ANALYSIS""; ""12.3 INFORMATION THEORYâ€?BASED FILTERING FOR NUMERIC DATA""; ""CATEGORICAL DATA""; ""12.5 WRAPPER-TYPE FEATURE SELECTION""; ""CONCLUSION""; ""REFERENCES""; ""Chapter 13 - Getting Started with RapidMiner""; ""13.1 USER INTERFACE AND TERMINOLOGY""; ""13.2 DATA IMPORTING AND EXPORTING TOOLS""; ""13.3 DATA VISUALIZATION TOOLS""; ""13.4 DATA TRANSFORMATION TOOLS""; ""13.5 SAMPLING AND MISSING VALUE TOOLS""; ""CONCLUSION""; ""REFERENCES""
  • ""Comparison of Data Mining Algorithms""

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