262 lines
9.9 KiB
TeX
262 lines
9.9 KiB
TeX
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\documentclass[]{report}
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\usepackage{graphicx}
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\usepackage{float}
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\usepackage{enumitem}
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\usepackage{tabularx}
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\usepackage{hyperref}
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\usepackage[normalem]{ulem}
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\usepackage{listings}
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\usepackage[most]{tcolorbox}
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\definecolor{commentsColor}{rgb}{0.497495, 0.497587, 0.497464}
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\definecolor{keywordsColor}{rgb}{0.000000, 0.000000, 0.635294}
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\definecolor{stringColor}{rgb}{0.558215, 0.000000, 0.135316}
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\lstset{
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columns=flexible,
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breaklines=true,
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backgroundcolor=\color{white}, % choose the background color
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basicstyle=\small\ttfamily, % the size of the fonts that are used for the code
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breakatwhitespace=false, % sets if automatic breaks should only happen at whitespace
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breaklines=true, % sets automatic line breaking
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captionpos=b, % sets the caption-position to bottom
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commentstyle=\color{commentsColor}\textit, % comment style
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deletekeywords={}, % if you want to delete keywords from the given language
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escapeinside={\%*}{*)}, % if you want to add LaTeX within your code
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extendedchars=true, % lets you use non-ASCII characters; for 8-bits encodings only, does not work with UTF-8
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%frame=tb, % adds a frame around the code
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keepspaces=true, % keeps spaces in text, useful for keeping indentation of code (possibly needs columns=flexible)
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keywordstyle=\color{keywordsColor}\bfseries, % keyword style
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language=C++, % the language of the code (can be overrided per snippet)
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otherkeywords={rank\_t, customerID\_t, distance\_t, fitness\_t}, % if you want to add more keywords to the set
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numbers=left, % where to put the line-numbers; possible values are (none, left, right)
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numbersep=5pt, % how far the line-numbers are from the code
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numberstyle=\tiny\color{commentsColor}, % the style that is used for the line-numbers
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rulecolor=\color{black}, % if not set, the frame-color may be changed on line-breaks within not-black text (e.g. comments (green here))
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showspaces=false, % show spaces everywhere adding particular underscores; it overrides 'showstringspaces'
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keepspaces=true,
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showstringspaces=false, % underline spaces within strings only
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showtabs=false, % show tabs within strings adding particular underscores
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stepnumber=1, % the step between two line-numbers. If it's 1, each line will be numbered
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stringstyle=\color{stringColor}, % string literal style
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tabsize=4, % sets default tabsize to 2 spaces
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title=\lstname, % show the filename of files included with \lstinputlisting; also try caption instead of title
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columns=fixed % Using fixed column width (for e.g. nice alignment)
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}
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\lstMakeShortInline|
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\newtcolorbox{answerbox}[2][]{%
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attach boxed title to top center
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colback = black!5!white,
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colframe = black!75!black,
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fonttitle = \bfseries,
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colbacktitle = gray!85!black,
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title = #2,#1,
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enhanced,
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}
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\lstset{
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basicstyle=\small\ttfamily,
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columns=flexible,
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breaklines=true
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}
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\usepackage{float}
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\renewcommand{\thesection}{\arabic{section}}
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% Title Page
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\title{\textbf{COSC 4P82 Assignment 1}}
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\author{\textbf{Brett Terpstra}\\
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bt19ex@brocku.ca - 692021}
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\begin{document}
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\maketitle
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\tableofcontents
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\section{Introduction}
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\section{Symbolic regression}
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\subsection{Introduction}
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\subsection{Parameter Table}
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\begin{center}
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\begin{tabularx}{0.8\textwidth}{ | >{\centering\arraybackslash}X | >{\centering\arraybackslash}X | }
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\hline
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Parameter & Value \\ [0.25ex]
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\hline\hline
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Runs & 10 \\
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\hline
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Population Size & 5000 \\
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\hline
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Generations & 50 \\
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\hline
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Training Set & N/A \\
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\hline
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Testing Set & N/A \\
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\hline
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Crossover Operator & Subtree Crossover\\
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\hline
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Mutation Operator & Grow Tree, Max Depth 4 \\
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\hline
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Crossover Rate & 0.9 or 1.0* \\
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\hline
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Mutation Rate & 0.1 or 1.0* \\
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\hline
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Elitism & Best 2 or 0 individuals Survive* \\
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\hline
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Selection & Fitness Proportionate \\
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\hline
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Function Set & *, /, +, -, exp, log, sin, cos \\
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\hline
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Terminal Set & X, Ephemeral Value \\
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\hline
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Tree Initialization & Half and Half, Max Depth 2-6 \\
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\hline
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Max Tree Depth & 17 \\
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\hline
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Raw Fitness & See Fitness Evaluation \\
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\hline
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Standardized Fitness & = Raw Fitness \\
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\hline
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\end{tabularx}
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\end{center}
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*4 Tests were run, 0.9 crossover, 0.9 mutation with 0 elitism and 2 elitism, and 1.0 crossover, 1.0 mutation with 0 elitism and 2 elitism.
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\subsection{Fitness Evaluation}
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Fitness is evaluated by taking the absolute value of the predicted y value minus the actual y value.
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If the difference is less than a user provided (default 1.e15) value cutoff it is added to the fitness value. If the difference value is less than the float epsilon value (\~= 0) the number of hits is incremented. Lower fitness values are preferred.
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\subsection{Fitness Plots}
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\begin{figure}[H]
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\centering
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\includegraphics[width=1.0\linewidth]{fp5}
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\caption{2 Elites, 10 Runs Averaged}
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\label{fig:fp4}
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\end{figure}
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\begin{figure}[H]
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\centering
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\includegraphics[width=1.0\linewidth]{fp3}
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\caption[]{0 Elites, 10 Runs Averaged}
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\label{fig:fp2}
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\end{figure}
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\subsection{Analysis and Conclusion}
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The best average fitness of all the tests was 0.19384 using 0.9 crossover and 0.1 mutation.
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\section{Rice Classification}
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\subsection{Introduction}
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\subsection{Parameter Table}
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\begin{center}
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\begin{tabularx}{0.8\textwidth}{ | >{\centering\arraybackslash}X | >{\centering\arraybackslash}X | }
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\hline
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Parameter & Value \\ [0.25ex]
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\hline\hline
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Runs & 10 \\
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\hline
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Population Size & 5000 \\
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\hline
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Generations & 51 \\
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\hline
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Training Set & Rice Classification (Cammeo and Osmancik) \\
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\hline
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Testing Set & Rice Classification (Cammeo and Osmancik) \\
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\hline
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Crossover Operator & Subtree Crossover\\
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\hline
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Mutation Operator & Grow Tree, Max Depth 4 \\
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\hline
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Crossover Rate & 0.9 or 0.9* \\
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\hline
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Mutation Rate & 0.1 or 0.9* \\
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\hline
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Elitism & Best 2 individuals Survive \\
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\hline
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Selection & Fitness Proportionate \\
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\hline
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Function Set & *, /, +, -, exp, log \\
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\hline
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Terminal Set & area, perimeter, major, minor, eccentricity, convex, extent, Ephemeral Value \\
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\hline
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Tree Initialization & Half and Half, Max Depth 2-6 \\
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\hline
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Max Tree Depth & 17 \\
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\hline
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Raw Fitness & See Fitness Evaluation \\
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\hline
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Standardized Fitness & = Raw Fitness \\
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\hline
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\end{tabularx}
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\end{center}
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\subsection{Fitness Evaluation}
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Tested on the input terminal values the GP produces a positive or negative value which is interpreted as either Cammeo (+) or Osmancik (-). Raw fitness is equal to the number of hits which is the number of correct identifications. The adjusted fitness is then calculated and subtracted from 1 in order to invert and produce the required lowest fitness better.
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\subsection{Fitness Plots}
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\begin{figure}[H]
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\centering
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\includegraphics[width=1.0\linewidth]{fp6}
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\caption{2 Elites, 10 Runs Averaged}
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\label{fig:fp6}
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\end{figure}
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\begin{figure}[H]
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\centering
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\includegraphics[width=1.0\linewidth]{fp7}
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\caption{2 Elites, 10 Runs Averaged}
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\label{fig:fp7}
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\end{figure}
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\subsection{Confusion Matrix}
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\begin{figure}[H]
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\centering
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\includegraphics[width=1.0\linewidth]{fp10}
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\caption{0.9 Crossover 0.1 Mutation 2 Elites Best Program Results}
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\label{fig:fp10}
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\end{figure}
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\begin{figure}[H]
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\centering
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\includegraphics[width=1.0\linewidth]{fp11}
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\caption{0.9 Crossover 0.1 Mutation 2 Elites 10 Run Average Results}
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\label{fig:fp11}
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\end{figure}
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\begin{figure}[H]
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\centering
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\includegraphics[width=1.0\linewidth]{fp12}
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\caption{0.9 Crossover 0.9 Mutation 2 Elites Best Program Results}
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\label{fig:fp8}
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\end{figure}
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\begin{figure}[H]
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\centering
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\includegraphics[width=1.0\linewidth]{fp13}
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\caption{0.9 Crossover 0.9 Mutation 2 Elites 10 Run Average Results}
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\label{fig:fp9}
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\end{figure}
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\subsection{Analysis and Conclusion}
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The best results found was a correct classification rate of 91.9\%. On average the 0.9 crossover with 0.1 mutation produced the best results with the 0.9/0.9 best result almost being equal.
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\section{Compiling / Executing}
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This assignment was made for linux using GCC 13.2.0, however any C++17 compliant compiler should work.
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The minimum GCC version appears to be 8.5, meaning this assignment can be built on sandcastle.
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\begin{lstlisting}
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cd your_path_to_this_source/
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mkdir build
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cd build
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cmake ../
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make -j 32
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\end{lstlisting}
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The actual assignment executable is called |Assignment_1| while the automatic run system is called |Assignment_1_RUNNER|. |Assignment_1_RUNNER| has a help menu with options but the defaults will work assuming you run from the build directory and are using part b only. If you want to build for Part A run |cmake -DPART_B=OFF| and run |Assignment_1_RUNNER| with |-b|
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\section{Conclusion}
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I made a few changes to lilgp, mostly memory fixes along with elitism with a number of individuals instead of a proportion. There appear to be some kind of issue in the GP, of which won't matter as assignment two will likely use my own gp system. I might look into it, but I was not aware there was an issue until compiling the stats here. My results have been generally positive, however, I did notice in the course of collecting data that at some point the Part A results stopped being consistently good however part B results have remained unchanged. Might have happened when I changed my custom random number seeder to not produce div by zero errors during testing. Could be anything. I don't like writing reports and have procrastinated on writing and instead have spent the last couple of weeks messing around with the GP. Fun fact a bunch of additions to my standard lib were made for this assignment. Next time will be better hopefully
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\section{References}
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Next assignment these will be proper. Latex is being annoying to setup for bib.\\\\
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https://archive.ics.uci.edu/dataset/545/rice+cammeo+and+osmancik\\
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http://garage.cse.msu.edu/software/lil-gp/
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\end{document}
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