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Data Analytics: Models and Algorithms for Intelligent Data Analysis by Thomas A. Runkler (auth.) is a nonfiction available to read on EtoBox.

What is Data Analytics: Models and Algorithms for Intelligent Data Analysis about?

Preface 5 Contents 6 Chapter 1 Introduction 9 1.1 It’s All About Data 9 1.2 Data Analytics, Data Mining, and Knowledge Discovery 10 Chapter 2 Data and Relations 12 2.1 The Iris Data Set 12 2.2 Data Scales 14 2.3 Set and Matrix Representations 16 2.4 Relations 17 2.5 Dissimilarity Measures 18 2.6 Similarity Measures 20 2.7 Sequence Relations 22 2.8 Sampling and Quantization 24 Chapter 3 Data Preprocessing 28 3.1 Error Types 28 3.2 Error Handling 31 3.3 Filtering 32 3.4 Data Transformation 37 3.5 Data Merging 40 Chapter 4 Data Visualization 42 4.1 Diagrams 42 4.2 Principal Component Analysis 44 4.3 Multidimensional Scaling 48 4.4 Sammon Mapping 51 4.5 Auto-Associator 54 4.6 Histograms 55 4.7 Spectral Analysis 57 Chapter 5 Correlation 62 5.1 Linear Correlation 62 5.2 Correlation and Causality 64 5.3 Chi-Square Test for Independence 65 Chapter 6 Regression 69 6.1 Linear Regression 69 6.2 Linear Regression with Nonlinear Substitution 73 6.3 Robust Regression 74 6.4 Neural Networks 74 6.5 Radial Basis Function Networks 78 6.6 Cross-Validation 80 6.7 Feature Selection 82 Chapter 7 Forecasting 85 7.1 Finite State Machines 85 7.2 Recurrent Models 86 7.3 Autoregressive Models 88 Chapter 8

Who reads Data Analytics: Models and Algorithms for Intelligent Data Analysis?

Author

Thomas A. Runkler (auth.)

Publisher

Vieweg+Teubner Verlag

Published

2012

Language

EN

Category

nonfiction