Leseprobe
Contents
Acknowledgments
Abstract
1. Introduction
1.1. Motivation
1.2. Outline
1.3. The Goal
1.4. Methodology
2. Theory Section
2.1. Gaussian Mixture Model
2.2. Dirichlet Process GMM
2.3. Hierarchical Clustering
3. Implementation
3.1. Software Specification
3.2. Data and Sensors
3.3. Data Visualisation and Inspection
3.4. Sensor values Discretisation and Extraction
3.5. Unsupervised Event Extraction
3.6. Data Structure for Event Analysis
3.7. Data Quality and Quantity
3.8. Predictive Analysis
3.8.1. Hourly Binning Analysis
3.8.2. Clustering Analysis
3.8.2.1. Hierarchical Clustering Analysis
3.8.2.2. Dirichlet Process Gaussian Mixture Model Clustering Analysis
4. Summary
4.1. Results
4.2. Discussion
Literature
List of Figures
List of Tables
List of Abbreviations
- Arbeit zitieren
- Dzenan Hamzic (Autor:in), 2016, AAL Data Cluster Analysis. Theory and Implementation, München, GRIN Verlag, https://www.grin.com/document/340200
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