Probleme mit der Ausrichtung mehrerer Zeilen

Probleme mit der Ausrichtung mehrerer Zeilen

Ich habe es satt, die Ausrichtung der letzten beiden Spalten und ihrer Mehrfachzeilen zu korrigieren

Ich will

21 dimensions reduced to 9 dimensions

kommt genau nebeneinander zu

Combine accuracy
of 9 dimensional reduced 
Feature Vector is 80\%

ÄHNLICH

9 dimensions Further
reduced to 7 dimensions

kommt Seite an Seite zu

Combine accuracy
of 7 dimensional reduced    
Feature Vector is 88\%

Ähnlich verhält es sich mit der letzten „Zeile“

Ausgabebild

\documentclass[journal]{IEEEtran}
%\usepackage{array} % loaded twice
\usepackage{multicol}
\usepackage{graphicx}
\usepackage{rotating}% added, for rothead
\usepackage{array, makecell, multirow, tabu}%merged in one line
%\newcolumntype{L}[1]{>{\raggedright\let\newline\\\arraybackslash\hspace{0pt}}m{#1}} % not used
%\newcolumntype{C}[1]{>{\centering\let\newline\\\arraybackslash\hspace{0pt}}m{#1}}
\newcolumntype{C}[1]{>{\centering\arraybackslash}m{#1}}% in this table is better use this definition
\begin{document}
\begin{table*}
  \settowidth\rotheadsize{DIMENSIONS}
  \renewcommand\multirowsetup{\centering} 
  \renewcommand{\arraystretch}{1.5}
  \centering
  \caption{Extreme Learning Machine(ELM) with kernel classifier accuracy of
  combine reduced feature vectors whose individual classifier accuracy was low}
  \begin{tabular}{|l|l|r|C{1.5cm}|C{1.5cm}|C{1.5cm}|C{2cm}|C{2.5cm}|}
    \hline 
    Algorithm
    & Dimension
        &  \multirow{6}{*}{\rothead{ADD THESE\\ DIMENSIONS}}
            & Total after Adding Dimensions
                & Classifier
                    & Dimension Reduction Technique
                        & Reduced Dimension
                            & Accuracy  \\ 
    \cline{1-2} \cline{4-8}
LBP & 4D    &
              & \multirow{5}{=}{4D + 6D + 4D\\ + 3D + 4D = 21D}
                 & \multirow{5}{=}{ELM with RBF kernel}
                     & \multirow{4}{=}{Eigenvalue as Dimension Estimator,
                                          PCA as Dimension Reduction}
                         & \multirow{4}{=}{21 dimensions reduced to 9 
dimensions}                                        \newline
                               & \multirow{4}{=}{Combine accuracy
                                                 of 9 dimensional reduced 
                                                 Feature Vector is 
80\%}\smallskip\newline \\
    \cline{1-2}
RGLBP  & 6D    &   &   &   &  &\multirow{5}{=}{9 dimensions Further
                                                  reduced to 7 dimensions} 
                                           &\multirow{5}{=}{Combine accuracy
                                                           of 7 dimensional 
reduced    
                                                           Feature Vector is 
88\% } \newline       \\
    \cline{1-2}
BDIP   & 4D    &   &   &   &   &\multirow{7}{=}{7 dimensions Further
                                                  reduced to 6 dimensions}    
                                    &\multirow{7}{=}{Combine accuracy of 6 
                                                   dimensional reduced 
                                                   Feature Vector is 100\% }\newline   \\
    \cline{1-2} 
HOG      & 3D    &   &   &    &   &   &   \\
    \cline{1-2} 
Combine and     & 4D    &   &   &    &   &   &    \\ 
reduced fv of   &       &   &   &       &   &   &  \\ 
poor individual  &       &   &   &       &   &   & \\   
 accuracy algorithms   &       &   &   &       &   &   & \\  
    \hline
\end{tabular}
\label{table:table6}
\end{table*}
\end{document}    

Antwort1

Anstatt sich mit \multirowder Ausrichtung zu beschäftigen, denke ich, dass das gewünschte Ergebnis leichter durch einige tabulars innerhalb von tabulars erreicht werden könnte.

\documentclass[journal]{IEEEtran}
\usepackage{multicol}
\usepackage{graphicx}
\usepackage{array, makecell}
\renewcommand{\arraystretch}{1.5}
\newcolumntype{L}[1]{>{\raggedright\arraybackslash}p{#1}} 
\newcolumntype{C}[1]{>{\centering\arraybackslash}m{#1}}% in this table is better use this definition
\newcolumntype{P}[1]{>{\centering\arraybackslash}p{#1}}

\begin{document}
\begin{table*}
\centering
\caption{Extreme Learning Machine(ELM) with kernel classifier accuracy of
  combine reduced feature vectors whose individual classifier accuracy was 
  low\label{table:table6}}
\begin{tabular}{|L{2cm}|L{1.3cm}|r|C{2.2cm}|C{1.5cm}|C{1.5cm}|C{2cm}|C{2.5cm}|} 
    \hline 
    Algorithm
    & Dimension
        &   & Total after Adding Dimensions
                & Classifier
                    & Dimension Reduction Technique
                        & Reduced Dimension
                            & Accuracy  \\ 
    \cline{1-2} \cline{4-8}
    \multicolumn{2}{@{}c@{}}{% first "sub"-table
            \begin{tabular}{|L{2cm}|L{1.3cm}|}
                LBP & 4D  \\[4.1pt]
                \hline
                RGLBP  & 6D  \\[4.1pt]
                 \hline
                BDIP   & 4D \\[4.1pt]
                \hline
                HOG      & 3D \\[4.1pt]
                \hline
                Combine and reduced fv of  poor individual accuracy algorithms & 4D \\
            \end{tabular}%
            }
        & \rotatebox[origin=c]{90}{\makecell{ADD THESE\\ DIMENSIONS}}
            & \multicolumn{5}{@{}c@{}}{% second "sub"-table
            \begin{tabular}{C{2.2cm}|C{1.5cm}|C{1.5cm}|C{2cm}|C{2.5cm}|}
                \makecell{4D + 6D + 4D\\ + 3D + 4D = 21D} 
                    & ELM with RBF kernel 
                        & Eigenvalue as Dimension Estimator, PCA as Dimension Reduction
                            & \multicolumn{2}{@{}c@{}}{% third "sub"-table (sub-table of the second sub-table)
                                \begin{tabular}{P{2cm}|P{2.5cm}|}
                                    21 dimensions reduced to 9 dimensions
                                        & Combine accuracy of 9 dimensional reduced Feature Vector is 80\% \\
                                    9 dimensions Further reduced to 7 dimensions
                                        & Combine accuracy of 7 dimensional reduced Feature Vector is 88\% \\
                                    7 dimensions Further reduced to 6 dimensions
                                        & Combine accuracy of 6 dimensional reduced Feature Vector is 100\%  \\
                                \end{tabular}%
                                }
            \end{tabular}
            } \\
   \hline
\end{tabular}
\end{table*}
\end{document}

Bildbeschreibung hier eingeben

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