From 99f0df9d41d40470814a06b2fd01d858ccaa56a4 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Oliver=20Sch=C3=BCtz?= Date: Sun, 8 Dec 2024 19:45:01 +0100 Subject: [PATCH] Methods --- .gitignore | 21 ++++- media/corr.png | Bin 0 -> 49242 bytes media/models.png | Bin 0 -> 21709 bytes out/CDS1011_A2.pdf | Bin 122156 -> 118781 bytes term-paper/CDS1011_A2.bbl | 83 ++++++++++++++++++ term-paper/packages_and_configuration.tex | 6 +- term-paper/research_questions_methodology.tex | 34 ++++++- 7 files changed, 140 insertions(+), 4 deletions(-) create mode 100644 media/corr.png create mode 100644 media/models.png create mode 100644 term-paper/CDS1011_A2.bbl diff --git a/.gitignore b/.gitignore index 7e144ff..c336c17 100644 --- a/.gitignore +++ b/.gitignore @@ -172,5 +172,24 @@ cython_debug/ # be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore # and can be added to the global gitignore or merged into this file. 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+}{% +{\protect \APACyear {{\protect \bibnodate {}}}}% +}]{% +alagoz_comparative_2024} +\APACinsertmetastar {% +alagoz_comparative_2024}% +\begin{APACrefauthors}% +Alagoz, C.% +\end{APACrefauthors}% +\unskip\ +\newblock +\APACrefYearMonthDay{{\protect \bibnodate {}}}{}{}. +\newblock +\APACrefbtitle {Comparative Analysis of {XGBoost} and Minirocket Algortihms for Human Activity Recognition} {Comparative analysis of {XGBoost} and minirocket algortihms for human activity recognition}\ (\BNUM\ {arXiv}:2402.18296). +\newblock +\APACaddressPublisher{}{{arXiv}}. +\newblock +\begin{APACrefURL} [{2024-12-01}]\url{http://arxiv.org/abs/2402.18296} \end{APACrefURL} +\newblock +\begin{APACrefDOI} \doi{10.48550/arXiv.2402.18296} \end{APACrefDOI} +\PrintBackRefs{\CurrentBib} + +\bibitem [\protect \citeauthoryear {% +Brownlee% +}{% +Brownlee% +}{% +{\protect \APACyear {{\protect \bibnodate {}}}}% +}]{% +brownlee_gentle_2018} +\APACinsertmetastar {% +brownlee_gentle_2018}% +\begin{APACrefauthors}% +Brownlee, J.% +\end{APACrefauthors}% +\unskip\ +\newblock +\APACrefYearMonthDay{{\protect \bibnodate {}}}{}{}. +\newblock +\APACrefbtitle {A Gentle Introduction to a Standard Human Activity Recognition Problem.} {A gentle introduction to a standard human activity recognition problem.} +\newblock +\begin{APACrefURL} [{2024-12-01}]\url{https://www.machinelearningmastery.com/how-to-load-and-explore-a-standard-human-activity-recognition-problem/} \end{APACrefURL} +\PrintBackRefs{\CurrentBib} + +\bibitem [\protect \citeauthoryear {% +Sikder% +, Chowdhury% +, Arif% +\BCBL {}\ \BBA {} Nahid% +}{% +Sikder% +\ \protect \BOthers {.}}{% +{\protect \APACyear {{\protect \bibnodate {}}}}% +}]{% +sikder_human_2021} +\APACinsertmetastar {% +sikder_human_2021}% +\begin{APACrefauthors}% +Sikder, N.% +, Chowdhury, M\BPBI S.% +, Arif, A\BPBI S\BPBI M.% +\BCBL {}\ \BBA {} Nahid, A\BHBI A.% +\end{APACrefauthors}% +\unskip\ +\newblock +\APACrefYearMonthDay{{\protect \bibnodate {}}}{}{}. +\newblock +\APACrefbtitle {Human Activity Recognition Using Multichannel Convolutional Neural Network} {Human activity recognition using multichannel convolutional neural network}\ (\BNUM\ {arXiv}:2101.06709). +\newblock +\APACaddressPublisher{}{{arXiv}}. +\newblock +\begin{APACrefURL} [{2024-12-01}]\url{http://arxiv.org/abs/2101.06709} \end{APACrefURL} +\newblock +\begin{APACrefDOI} \doi{10.48550/arXiv.2101.06709} \end{APACrefDOI} +\PrintBackRefs{\CurrentBib} + +\end{thebibliography} diff --git a/term-paper/packages_and_configuration.tex b/term-paper/packages_and_configuration.tex index 5e18343..e7b624b 100644 --- a/term-paper/packages_and_configuration.tex +++ b/term-paper/packages_and_configuration.tex @@ -10,10 +10,12 @@ \usepackage{hyperref} \usepackage{apacite} \usepackage{tabularx} -\usepackage[affil-it]{authblk} +\usepackage[affil-it]{authblk} %\usepackage{newtxtext} %\usepackage{newtxmath} \usepackage{newtx} +\usepackage{graphicx} +\usepackage{float} \usepackage{multicol} @@ -36,4 +38,4 @@ pdfborder=0 0 0 } -\bibliographystyle{apacite} \ No newline at end of file +\bibliographystyle{apacite} diff --git a/term-paper/research_questions_methodology.tex b/term-paper/research_questions_methodology.tex index 842f55e..92c978c 100644 --- a/term-paper/research_questions_methodology.tex +++ b/term-paper/research_questions_methodology.tex @@ -2,7 +2,39 @@ %! Date = 01.12.24 % Preamble + \section{Forschungsfragen und Methodik}\label{sec:forschungsfragen-und-methodik} Die Forschungsfrage lautet, wie zuverlässig können Aktivitäten anhand von Smartphone Sensordaten erkannt werden. -Als Basis diente ein Basisdatensatz~\cite{sikder_human_2021}. \ No newline at end of file +Als Basis dieser Analyse, diente der Datensatz "UCI Human Activity Recognition (HAR) Dataset" \cite{sikder_human_2021}. Dieser enthält Aktivitäten, gelabelt nach Sensordaten von Smartphones (Samsung Galaxy S II). Die Daten stammen von 30 Probanden im Alter von 19 bis 48 Jahren, die sechs vordefinierte Aktivitäten ausführten: + +\begin{itemize} + \item WALKING (Gehen) + \item WALKING\_UPSTAIRS (Treppe hinaufgehen) + \item WALKING\_DOWNSTAIRS (Treppe hinuntergehen) + \item SITTING (Sitzen) + \item STANDING (Stehen) + \item LAYING (Liegen) +\end{itemize} + +Der Datensatz wurde bereits in einen Test und Trainingsset unterteilt, wobei das Trainingsset 70\% und das Testset 30\% der Daten enthält. +Eine Datenaufbereitung war jedoch notwending, da manche Features einen für Pandas nicht eindeutigen Namen hatten. +Die folgenden zwei Features wurden als identisch gewertet: +\begin{itemize} + \item fBodyGyro-bandsEnergy()-33,40 + \item fBodyGyro-bandsEnergy()-41,48 +\end{itemize} + +Da der Datensatz eine hohe anzahl an Features enthält, wurde eine Feature Selection durchgeführt, um die Anzahl der Features zu reduzieren. Hierzu wurde die Korrelation jedes Features mit der Aktivität berechnet und die 20 Features mit der höchsten positiven und negativen Korrelation ausgewählt. +\begin{figure}[H] + \centering + \includegraphics[width=0.8\textwidth]{../media/corr.png} + \caption{Korrelation der Features mit der Aktivität} +\end{figure} + +Damit wurden 3 Modelle trainiert und mit dem F1-Score evaluiert: +\begin{figure}[H] + \centering + \includegraphics[width=0.8\textwidth]{../media/models.png} + \caption{Modelle und deren F1-Score} +\end{figure}