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yslides.tex
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\documentclass[10pt, xcolor=dvipsnames]{beamer}
\usepackage[utf8]{inputenc}
% \documentclass[10pt,xcolor=pst]{beamer}
%\usepackage[head=14pt,text={5.5in,8in},centering]{geometry}
%From book.tex
\usepackage{xNGmacro}
\input{xpackages}
\usepackage{xrlocal}
%from book.tex
%\usepackage{standalone}
%\usepackage{etex}
%\usepackage{pst-all,pst-func}
%\usepackage{pst-solides3d,pst-3dplot,pst-vue3d,pst-bar}
%\usepackage{pst-eucl}
%\usepackage{pstricks,auto-pst-pdf} % works
%\usepackage{auto-pst-pdf} % works
%\usepackage[pdf]{pstricks}
%\usepackage{pst-tree}
\input{xsymboldefs}
%%%%FOR TOP ALIGNED CELLS IN TABULAR%%%%%%%%
\newsavebox\topalignbox
\newcolumntype{T}{%
>{\begin{lrbox}\topalignbox
\rule{0pt}{\ht\strutbox}}
c
<{\end{lrbox}%
\raisebox{\dimexpr-\height+\ht\strutbox\relax}%
{\usebox\topalignbox}}}
\newcolumntype{M}{>{$\vcenter\bgroup\hbox\bgroup}c<{\egroup\egroup$}}
\usetheme{Madrid}
\usecolortheme{default}
\usefonttheme{default}
%\definecolor{myorange}{HTML}{CA1B00}
%\definecolor{myorange}{HTML}{D53212} %RGB 213,50,18
%\definecolor{myorange}{RGB}{223,72,20}
%\setbeamercolor*{palette primary}{use=structure,fg=white,bg=myorange}
%\setbeamercolor*{palette secondary}{use=structure,fg=white,bg=myorange}
%\setbeamercolor*{palette tertiary}{use=structure,fg=white,bg=myorange}
%\setbeamercolor*{palette quaternary}{use=structure,fg=white,bg=myorange}
%\setbeamercolor{frametitle}{bg=myorange}
%\setbeamercolor{block title}{bg=myorange}
%\definecolor{myblue}{RGB}{95,134,192}
% \definecolor{myblue}{RGB}{63,187,228}
\definecolor{myblue}{RGB}{31,148,207}
\setbeamercolor*{palette primary}{use=structure,fg=white,bg=myblue}
\setbeamercolor*{palette secondary}{use=structure,fg=white,bg=myblue}
\setbeamercolor*{palette tertiary}{use=structure,fg=white,bg=myblue}
\setbeamercolor*{palette quaternary}{use=structure,fg=white,bg=myblue}
\setbeamercolor{frametitle}{bg=myblue}
\setbeamercolor{block title}{bg=myblue}
\title[Data Mining and Machine Learning]{Data Mining and Machine Learning:\\Fundamental Concepts and Algorithms}
\subtitle{dataminingbook.info}
\author[Zaki \& Meira Jr.]{Mohammed J. Zaki\inst{1} \and
Wagner Meira Jr.\inst{2}}
\institute[RPI and UFMG]{
\inst{1}Department of Computer Science\\ Rensselaer Polytechnic
Institute, Troy, NY, USA
\and
\inst{2}Department of Computer Science\\Universidade Federal de Minas
Gerais, Belo Horizonte, Brazil\\
}
\begin{document}
%\includeonlylecture{xnumeric}
%introduction
%exploratory data analysis
\graphicspath{{./}{./EDA/data}{./EDA/numeric/}{./EDA/categorical/}{./EDA/datareduction/}{./EDA/highdim/}{./EDA/dimreduction/}{./EDA/densityestimation/}}
%\include{EDA/part}
\ifdefined\doxdata \include{EDA/data/ydata} \fi
\ifdefined\doxnum \include{EDA/numeric/ynumeric} \fi
\ifdefined\doxcat \include{EDA/categorical/ycategorical} \fi
\ifdefined\doxgraph \include{EDA/graph/ygraph} \fi
\ifdefined\doxkernel \include{EDA/kernel/ykernel} \fi
\ifdefined\doxhighdim \include{EDA/highdim/yhighdim} \fi
\ifdefined\doxdimred \include{EDA/dimreduction/ydimreduction} \fi
%frequent pattern mining
\graphicspath{{./FPM/fpmover/}{./FPM/itemsets/}{./FPM/sumrep/}{./FPM/sequences/}{./FPM/graphs/}{./FPM/fpmeval/}}
%\include{FPM/part}
\ifdefined\doxitemsets \include{FPM/itemsets/yitemsets} \fi
\ifdefined\doxsumrep \include{FPM/sumrep/ysumrep} \fi
\ifdefined\doxsequences \include{FPM/sequences/ysequences} \fi
\ifdefined\doxgraphs \include{FPM/graphs/ygraphs} \fi
\ifdefined\doxfpmeval \include{FPM/fpmeval/yfpmeval} \fi
%clustering
\graphicspath{{./CLUST/overview/}{./CLUST/density/}{./CLUST/representative/}{./CLUST/hierarchical/}{./CLUST/subspace/}{./CLUST/eval/}}
%\include{CLUST/part}
\ifdefined\doxrep \include{CLUST/representative/yrepresentative} \fi
\ifdefined\doxhier \include{CLUST/hierarchical/yhierarchical} \fi
\ifdefined\doxdens \include{CLUST/density/ydensity} \fi
\ifdefined\doxspectral \include{CLUST/spectral/yspectral} \fi
\ifdefined\doxclusteval \include{CLUST/eval/yeval} \fi
%classification
\graphicspath{{./CLASS/overview/}{./CLASS/instance/}{./CLASS/decisiontrees/}{./CLASS/rules/}{./CLASS/probabilistic/}{./CLASS/svm/}{./CLASS/eval/}{./CLASS/lda/}}
%\include{CLASS/part}
\ifdefined\doxprob \include{CLASS/probabilistic/yprobabilistic} \fi
\ifdefined\doxdectrees \include{CLASS/decisiontrees/ydecisiontrees} \fi
\ifdefined\doxlda \include{CLASS/lda/ylda} \fi
\ifdefined\doxsvm \include{CLASS/svm/ysvm} \fi
\ifdefined\doxclasseval \include{CLASS/eval/yeval} \fi
%regression
\graphicspath{{./REG/linear/}{./REG/logit/}{./REG/neural/}{./REG/deep/}{./REG/eval/}}
\ifdefined\doxlinear \include{REG/linear/ylinear} \fi
\ifdefined\doxlogit \include{REG/logit/ylogit} \fi
\ifdefined\doxneural \include{REG/neural/yneural} \fi
\ifdefined\doxdeep \include{REG/deep/ydeep} \fi
\ifdefined\doxevalreg \include{REG/eval/yeval} \fi
\begin{frame}
\titlepage
\end{frame}
\end{document}