LaTex:算法排版
排版可能需要的包:
usepackage{algorithm} //format of the algorithm
usepackage{algorithmic} //format of the algorithm
usepackage{multirow} //multirow for format of table
usepackage{amsmath}
usepackage{xcolor}
DeclareMathOperator*{argmin}{argmin} //argmin或argmax公式的排版
enewcommand{algorithmicrequire}{ extbf{Input:}} //Use Input in the format of Algorithm
enewcommand{algorithmicensure}{ extbf{Output:}} //UseOutput in the format of Algorithm
排版圖片可能需要的包:
usepackage{graphics}
usepackage{graphicx}
usepackage{epsfig}
算法的排版舉例:
\begin{algorithm}[htb] %算法的開始
caption{ Framework of ensemble learning for our system.} %算法的標題
label{alg:Framwork} %給算法一個標簽,這樣方便在文中對算法的引用
\begin{algorithmic}[1] %這個1 表示每一行都顯示數字
REQUIRE ~~\ %算法的輸入參數:Input
The set of positive samples for current batch, $P_n$;\
The set of unlabelled samples for current batch, $U_n$;\
Ensemble of classifiers on former batches, $E_{n-1}$;
ENSURE ~~\ %算法的輸出:Output
Ensemble of classifiers on the current batch, $E_n$;
STATE Extracting the set of reliable negative and/or positive samples $T_n$ from $U_n$ with help of $P_n$; label{code:fram:extract} %算法的一個陳述,對應算法的一個步驟或公式之類的; label{ code:fram:extract }對此行的標記,方便在文中引用算法的某個步驟
STATE Training ensemble of classifiers $E$ on $T_n cup P_n$, with help of data in former batches; label{code:fram:trainbase}
STATE $E_n=E_{n-1}cup E$; label{code:fram:add}
STATE Classifying samples in $U_n-T_n$ by $E_n$; label{code:fram:classify}
STATE Deleting some weak classifiers in $E_n$ so as to keep the capacity of $E_n$; label{code:fram:select}
RETURN $E_n$; %算法的返回值
end{algorithmic}
end{algorithm}
排版效果圖:
在文中對算法和算法的某個步驟的引用:Therefore, in step
ef{code:fram:extract} of algorithm
ef{alg:Framwork}, we extract $T_n$, a set of reliable negative samples
1、 For和While循環語句的排版舉例
(1) 排版效果圖
(2)排版代碼
\begin{algorithm}[h]
caption{An example for format For & While Loop in Algorithm}
\begin{algorithmic}[1]
FOR{each $iin [1,9]$}
STATE initialize a tree $T_{i}$ with only a leaf (the root);\
STATE $T=Tigcup T_{i};$\
ENDFOR
FORALL {$c$ such that $cin RecentMBatch(E_{n-1})$} label{code:TrainBase:getc}
STATE $T=T cup PosSample(c)$; label{code:TrainBase:pos}
ENDFOR;
FOR{$i=1$; $i<n$; $i++$ }
STATE $//$ Your source here;
ENDFOR
FOR{$i=1$ to $n$}
STATE $//$ Your source here;
ENDFOR
STATE $//$ Reusing recent base classifiers. label{code:recentStart}
WHILE {$(|E_n| leq L_1 )and( D
eq phi)$}
STATE Selecting the most recent classifier $c_i$ from $D$;
STATE $D=D-c_i$;
STATE $E_n=E_n+c_i$;
ENDWHILE label{code:recentEnd}
end{algorithmic}
end{algorithm}
from:?http://www.binghe.org/2010/03/latex-equation-and-numbering/
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