AAL Data Cluster Analysis. Theory and Implementation


Bachelor Thesis, 2016

57 Pages, Grade: 1


Excerpt


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

Excerpt out of 57 pages

Details

Title
AAL Data Cluster Analysis. Theory and Implementation
College
Vienna University of Technology
Grade
1
Author
Year
2016
Pages
57
Catalog Number
V340200
ISBN (eBook)
9783668299542
ISBN (Book)
9783668299559
File size
2193 KB
Language
English
Keywords
time-series, cluster analysis, gaussian mixture model, hierarchical clustering, predictive analysis, hourly binning, sci-kit, python
Quote paper
Dzenan Hamzic (Author), 2016, AAL Data Cluster Analysis. Theory and Implementation, Munich, GRIN Verlag, https://www.grin.com/document/340200

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