📄 synth.tr.html

📁 本程序是基于linux系统下c++代码

💻 HTML

字号:

<!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN">
<html><head><title>R: Synthetic Classification Problem</title>
<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
<link rel="stylesheet" type="text/css" href="../../R.css">
</head><body>

<table width="100%" summary="page for synth.tr {MASS}"><tr><td>synth.tr {MASS}</td><td align="right">R Documentation</td></tr></table>
<h2>Synthetic Classification Problem</h2>


<h3>Description</h3>

<p>
The <code>synth.tr</code> data frame has 250 rows and 3 columns.
The <code>synth.te</code> data frame has 100 rows and 3 columns.
It is intended that <code>synth.tr</code> be used from training and
<code>synth.te</code> for testing.
</p>


<h3>Usage</h3>

<pre>
synth.tr
synth.te
</pre>


<h3>Format</h3>

<p>
These data frames contains the following columns:
<dl>
<dt><code>xs</code></dt><dd>x-coordinate
</dd>
<dt><code>ys</code></dt><dd>y-coordinate
</dd>
<dt><code>yc</code></dt><dd>class, coded as 0 or 1.
</dd></dl>

<h3>Source</h3>

<p>
Ripley, B.D. (1994)
Neural networks and related methods for
classification (with discussion).
<EM>Journal of the Royal Statistical Society series B</EM>
<B>56</B>, 409&ndash;456.
</p>
<p>
Ripley, B.D. (1996)
<EM>Pattern Recognition and Neural Networks.</EM>
Cambridge: Cambridge University Press.
</p>



<hr><div align="center">[Package <em>MASS</em> version 7.2-44 <a href="00Index.html">Index]</a></div>

</body></html>

⌨️ 快捷键说明

复制代码 Ctrl + C

搜索代码 Ctrl + F

全屏模式 F11

切换主题 Ctrl + Shift + D

显示快捷键 ?

增大字号 Ctrl + =

减小字号 Ctrl + -