week3/eml.tex

   1 \documentclass[a4paper]{article}
   2
   3 \usepackage{amssymb}
   4 \usepackage{booktabs}
   5 \usepackage{float}
   6 \usepackage{geometry}
   7
   8 \title{Exercise: Machine Learning}
   9 \author{Mart Lubbers}
  10 \date{\today}
  11
  12 \begin{document}
  13 \maketitle
  14 \subsection*{Chapter 5: Machine Learning}
  15 \begin{table}[H]
  16         \centering
  17         \begin{tabular}{lll}
  18                 \toprule
  19                 Method & Correctly classified & Root relative squared error\\
  20                 \midrule
  21                 NaiveBayes & $96.6449\%$ & $35.7222\%$\\
  22                 NaiveBayes (10FCF) & $96.4352\%$ & $37.1926\%$\\
  23                 J48 & $96.6449\%$ & $34.9136\%$\\
  24                 J48 (10FCF) & $96.4352\%$ & $36.5122\%$\\
  25                 \bottomrule
  26         \end{tabular}
  27         \caption{Results for \texttt{P1D} and \texttt{FD}}
  28 \end{table}
  29
  30 \begin{table}[H]
  31         \centering
  32         \begin{tabular}{lllllll}
  33                 \toprule
  34                 \texttt{P2D} & \texttt{P1D} & \texttt{N2D} & \texttt{N1D} & \texttt{FW} & Correctly classified\\
  35                 \midrule
  36                 \checkmark{}    & \checkmark{}  & \checkmark{}  & \checkmark{}  & \checkmark{}  & $98.3225\%$\\
  37                 \checkmark{}    & \checkmark{}  & \checkmark{}  & \checkmark{}  &       & $97.3905\%$\\
  38                 \checkmark{}    & \checkmark{}  &       & \checkmark{}  & \checkmark{}  & $98.5555\%$\\
  39                 \checkmark{}    & \checkmark{}  &       & \checkmark{}  &       & $97.507\%$\\
  40                 \checkmark{}    & \checkmark{}  &       &       & \checkmark{}  & $98.0429\%$\\
  41                 \checkmark{}    & \checkmark{}  &       &       &       & $95.5732\%$\\
  42
  43                         & \checkmark{}  & \checkmark{}  & \checkmark{}  & \checkmark{}  & $\%$\\
  44                         & \checkmark{}  & \checkmark{}  & \checkmark{}  &       & $\%$\\
  45                         & \checkmark{}  &       & \checkmark{}  & \checkmark{}  & $\%$\\
  46                         & \checkmark{}  &       & \checkmark{}  &       & $\%$\\
  47                         & \checkmark{}  &       &       & \checkmark{}  & $98.2992\%$\\
  48                         & \checkmark{}  &       &       &       & $96.6449\%$\\
  49
  50                         &       & \checkmark{}  & \checkmark{}  & \checkmark{}  & $\%$\\
  51                         &       & \checkmark{}  & \checkmark{}  &       & $\%$\\
  52                         &       &       & \checkmark{}  & \checkmark{}  & $\%$\\
  53                         &       &       & \checkmark{}  &       & $\%$\\
  54                         &       &       &       & \checkmark{}  & $88.4436\%$\\
  55
  56                 \bottomrule
  57         \end{tabular}
  58         \caption{NaiveBayes}
  59 \end{table}
  60
  61 \subsection*{Chapter 6: Exercises}
  62 \begin{itemize}
  63         \item\emph{If we look at the Viterbi algorithm, we see that the
  64                 probability of state at a given position is calculated $n$ the basis of
  65                 the preceding $n$ states. However, it is claimed that the algorithm
  66                 takes into account the whole sequence. Explain in your own words (at
  67                 most $100$) how the probability is influenced by the rest of the
  68                 sequence, i.e.\ both the positions more than n back and the following
  69                 positions.}
  70
  71         \item\emph{Explain in your own words (at most 50) how the EM algorithm
  72                 works. I don't mean the mathematics, but the underlying concept.}
  73 \end{itemize}
  74 \end{document}