我正在嘗試對決策樹模型進行一些修改,其中tikz
取自這裡。我使用的程式碼與該帖子完全相同,唯一的變化是\documentclass[]{article}
代碼:
\documentclass[]{article}
\usepackage{forest}
\usetikzlibrary{fit,positioning}
\tikzset{
font=\Large\sffamily\bfseries,
red arrow/.style={
midway,red,sloped,fill, minimum height=3cm, single arrow, single arrow head extend=.5cm, single arrow head indent=.25cm,xscale=0.3,yscale=0.15,
allow upside down
},
black arrow/.style 2 args={-stealth, shorten >=#1, shorten <=#2},
black arrow/.default={1mm}{1mm},
tree box/.style={draw, rounded corners, inner sep=1em},
node box/.style={white, draw=black, text=black, rectangle, rounded corners},
}
\begin{document}
\begin{forest}
for tree={l sep=3em, s sep=3em, anchor=center, inner sep=0.7em, fill=blue!50, circle, where level=2{no edge}{}}
[
Training Data, node box
[sample and feature bagging, node box, alias=bagging, above=4em
[,red!70,alias=a1[[,alias=a2][]][,red!70,edge label={node[above=1ex,red arrow]{}}[[][]][,red!70,edge label={node[above=1ex,red arrow]{}}[,red!70,edge label={node[below=1ex,red arrow]{}}][,alias=a3]]]]
[,red!70,alias=b1[,red!70,edge label={node[below=1ex,red arrow]{}}[[,alias=b2][]][,red!70,edge label={node[above=1ex,red arrow]{}}]][[][[][,alias=b3]]]]
[~~$\dots$~,scale=2,no edge,fill=none,yshift=-4em]
[,red!70,alias=c1[[,alias=c2][]][,red!70,edge label={node[above=1ex,red arrow]{}}[,red!70,edge label={node[above=1ex,red arrow]{}}[,alias=c3][,red!70,edge label={node[above=1ex,red arrow]{}}]][,alias=c4]]]]
]
\node[tree box, fit=(a1)(a2)(a3)](t1){};
\node[tree box, fit=(b1)(b2)(b3)](t2){};
\node[tree box, fit=(c1)(c2)(c3)(c4)](tn){};
\node[below right=0.5em, inner sep=0pt] at (t1.north west) {Tree 1};
\node[below right=0.5em, inner sep=0pt] at (t2.north west) {Tree 2};
\node[below right=0.5em, inner sep=0pt] at (tn.north west) {Tree $n$};
\path (t1.south west)--(tn.south east) node[midway,below=4em, node box] (mean) {mean in regression or majority vote in classification};
\node[below=3em of mean, node box] (pred) {prediction};
\draw[black arrow={5mm}{4mm}] (bagging) -- (t1.north);
\draw[black arrow] (bagging) -- (t2.north);
\draw[black arrow={5mm}{4mm}] (bagging) -- (tn.north);
\draw[black arrow={5mm}{5mm}] (t1.south) -- (mean);
\draw[black arrow] (t2.south) -- (mean);
\draw[black arrow={5mm}{5mm}] (tn.south) -- (mean);
\draw[black arrow] (mean) -- (pred);
\end{forest}
\end{document}
我一直在嘗試做幾件事:
- 使
tikz
圖表適合 a\documentclass[]{article}
而不是 a\documentclass[tikz]{standalone}
- 我一直在嘗試更改顏色以匹配以下樹
終端節點的顏色為綠色和紅色,所有其他節點的顏色相同,但似乎無法弄清楚這部分(當前,當箭頭為紅色時,程式碼中的樹為紅色。我想保留箭頭但只需使所有顏色相同- 除了終端節點)。
- 我可以透過修改以下行來更改
circle
為,但結果是一個正方形。rectangle
for tree={l sep=3em, s sep=3em, anchor=center, inner sep=0.7em, fill=blue!50, rectangle, where level=2{no edge}{}}
編輯:
答案1
嗯,它太寬了,所以你需要把東西變窄。例如透過減少
s sep
.節點的顏色和箭頭的顏色沒有關聯,如果節點是紅色的,那是因為您已經
,red!70
為該特定節點添加了。所以你只需要刪除其中的很多,red!70
。您需要分別設定寬度和高度:
inner sep=0, minimum width=1em, minimum height=0.5em,
否inner sep
,因此沒有填充,然後將minimum width
/設定height
為合適的值。您可能想要修改它們。
我還在節點s sep
中進行了設置sample and feature bagging,
,以使子樹的間距更大一些,並添加了兩個phantom
節點以在第二個和第三個節點之間提供額外的空間。我添加了後者,透過在和\dots
之間放置一個節點。t2
tn
我可能會mean in regression..
直接在下面設定節點t2
,但我會將其留給您來決定。
此螢幕截圖中的框架是由showframe
套件製作的,表示文字區塊的寬度。
\documentclass[]{article}
\usepackage{
forest,
% showframe
}
\usetikzlibrary{fit,positioning}
\tikzset{
font=\large\sffamily\bfseries,
red arrow/.style={
midway,red,sloped,fill, minimum height=3cm, single arrow, single arrow head extend=.5cm, single arrow head indent=.25cm,xscale=0.3,yscale=0.15,
allow upside down
},
black arrow/.style 2 args={-stealth, shorten >=#1, shorten <=#2},
black arrow/.default={1mm}{1mm},
tree box/.style={draw, rounded corners, inner sep=1em},
node box/.style={white, draw=black, text=black, rectangle, rounded corners},
}
\begin{document}
\begin{center}
\begin{forest}
for tree={
l sep=2em,
s sep=2mm,
anchor=center,
inner sep=0,
minimum width=1em,
minimum height=0.5em,
fill=blue!50,
rectangle,
where level=2{no edge}{}}
[
Training Data, node box
[sample and feature bagging, node box, alias=bagging, above=4em,s sep=1.1cm
[,alias=a1[[,alias=a2][]][,edge label={node[above=1ex,red arrow]{}}[[][]]
[,edge label={node[above=1ex,red arrow]{}}[,red!70,edge label={node[below=1ex,red arrow]{}}][,alias=a3]]]]
[,alias=b1[,edge label={node[below=1ex,red arrow]{}}[[,alias=b2][]][,red!70,edge label={node[above=1ex,red arrow]{}}]][[][[][,alias=b3]]]]
[,phantom]
[,phantom]
[,alias=c1[[,alias=c2][]][,edge label={node[above=1ex,red arrow]{}}[,edge label={node[above=1ex,red arrow]{}}[,alias=c3][,red!70,edge label={node[above=1ex,red arrow]{}}]][,alias=c4]]]]
]
\node[tree box, fit=(a1)(a2)(a3)](t1){};
\node[tree box, fit=(b1)(b2)(b3)](t2){};
\node[tree box, fit=(c1)(c2)(c3)(c4)](tn){};
\begin{scope}[every node/.append style={below right=0.5em, inner sep=0pt, font=\normalsize\sffamily\bfseries}]
\node at (t1.north west) {Tree 1};
\node at (t2.north west) {Tree 2};
\node at (tn.north west) {Tree $n$};
\end{scope}
\path (t1.south west)--(tn.south east) node[midway,below=4em, node box] (mean) {mean in regression or majority vote in classification};
\node[below=3em of mean, node box] (pred) {prediction};
\draw[black arrow={5mm}{4mm}] (bagging) -- (t1.north);
\draw[black arrow] (bagging) -- (t2.north);
\draw[black arrow={5mm}{4mm}] (bagging) -- (tn.north);
\draw[black arrow={5mm}{5mm}] (t1.south) -- (mean);
\draw[black arrow] (t2.south) -- (mean);
\draw[black arrow={5mm}{5mm}] (tn.south) -- (mean);
\draw[black arrow] (mean) -- (pred);
\path (t2) -- node {\dots} (tn); % <-- new node
\end{forest}
\end{center}
\end{document}