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<span class="dt">rareCount=</span><span class="dv">0</span> <span class="co"># Note: usually want rareCount>0, setting to zero to illustrate problem</span>
<span class="dt">pruneSig=</span><span class="kw">c</span>() <span class="co"># Note: usually want pruneSig to be a small fraction, setting to null to illustrate problems</span>
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@@ -197,18 +197,18 @@ <h2>The Right Way: A Calibration Set</h2>
<span class="dt">rareCount=</span><span class="dv">0</span> <span class="co"># Note: usually want rareCount>0, setting to zero to illustrate problem</span>
<spanclass="dt">rareCount=</span><spanclass="dv">0</span><spanclass="co"># Note: usually want rareCount>0, setting to zero to illustrate problem</span>
<spanclass="dt">pruneSig=</span><spanclass="kw">c</span>() <spanclass="co"># Note: usually want pruneSig to be a small fraction, setting to null to illustrate problem</span>
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@@ -195,14 +195,14 @@ <h2>Correct Practice 1/2: Use different data to treat and train</h2>
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<spanclass="dt">rareCount=</span><spanclass="dv">0</span>, <spanclass="co"># Note set this to something larger, like 5</span>
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<spanclass="dt">rareSig=</span><spanclass="kw">c</span>() <spanclass="co"># Note set this to something like 0.3</span>
d <-<spanclass="st"></span><spanclass="kw">data.frame</span>(<spanclass="dt">x=</span>xVar,<spanclass="dt">y=</span>yVar,<spanclass="dt">stringsAsFactors =</span><spanclass="ot">FALSE</span>)
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