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    <title>topic Model Comparison Node - Lift Value in SAS Data Science</title>
    <link>https://communities.sas.com/t5/SAS-Data-Science/Model-Comparison-Node-Lift-Value/m-p/535469#M7658</link>
    <description>&lt;P&gt;Hello,&lt;/P&gt;&lt;P&gt;I am looking at the Output in Results after running a Model Comaprison node for four models. I understand how lift/gain/%response is calculated across deciles but was wondering how these values are calculated for the 'whole' model (see below - apologies about formatting).&amp;nbsp;&lt;/P&gt;&lt;P&gt;Thanks,&lt;/P&gt;&lt;P&gt;Martin&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Data Role=Valid&lt;BR /&gt;&lt;BR /&gt;Statistics Reg Tree Neural Tree2&lt;BR /&gt;&lt;BR /&gt;Valid: Kolmogorov-Smirnov Statistic 0.41 0.37 0.42 0.37&lt;BR /&gt;Valid: Average Squared Error 0.12 0.12 0.13 0.13&lt;BR /&gt;Valid: Roc Index 0.76 0.72 0.77 0.72&lt;BR /&gt;Valid: Average Error Function 0.39 . 0.40 .&lt;BR /&gt;Valid: Bin-Based Two-Way Kolmogorov-Smirnov Probability Cutoff 0.13 0.10 0.17 0.22&lt;BR /&gt;Valid: Cumulative Percent Captured Response 27.43 27.54 21.71 21.26&lt;BR /&gt;Valid: Percent Captured Response 13.14 10.91 8.00 10.53&lt;BR /&gt;Valid: Divisor for VASE 2100.00 2100.00 2100.00 2100.00&lt;BR /&gt;Valid: Error Function 820.57 . 833.16 .&lt;BR /&gt;Valid: Gain 174.29 175.41 117.14 112.60&lt;BR /&gt;Valid: Gini Coefficient 0.52 0.43 0.53 0.43&lt;BR /&gt;Valid: Bin-Based Two-Way Kolmogorov-Smirnov Statistic 0.39 0.36 0.41 0.36&lt;BR /&gt;Valid: Kolmogorov-Smirnov Probability Cutoff 0.12 0.08 0.10 0.08&lt;BR /&gt;Valid: Cumulative Lift 2.74 2.75 2.17 2.13&lt;BR /&gt;Valid: Lift 2.65 2.20 1.62 2.13&lt;BR /&gt;Valid: Maximum Absolute Error 0.97 0.93 0.99 0.93&lt;BR /&gt;Valid: Misclassification Rate 0.17 0.16 0.17 0.17&lt;BR /&gt;Valid: Mean Squared Error 0.12 . 0.13 .&lt;BR /&gt;Valid: Sum of Frequencies 1050.00 1050.00 1050.00 1050.00&lt;BR /&gt;Valid: Root Average Squared Error 0.35 0.35 0.35 0.35&lt;BR /&gt;Valid: Cumulative Percent Response 45.71 45.90 36.19 35.43&lt;BR /&gt;Valid: Percent Response 44.23 36.70 26.92 35.43&lt;BR /&gt;Valid: Root Mean Squared Error 0.35 . 0.35 .&lt;BR /&gt;Valid: Sum of Squared Errors 256.65 261.89 263.95 264.27&lt;BR /&gt;Valid: Sum of Case Weights Times Freq 2100.00 . 2100.00 .&lt;BR /&gt;Valid: Number of Wrong Classifications . . 181.00 .&lt;/P&gt;</description>
    <pubDate>Thu, 14 Feb 2019 01:09:43 GMT</pubDate>
    <dc:creator>MartinBoland</dc:creator>
    <dc:date>2019-02-14T01:09:43Z</dc:date>
    <item>
      <title>Model Comparison Node - Lift Value</title>
      <link>https://communities.sas.com/t5/SAS-Data-Science/Model-Comparison-Node-Lift-Value/m-p/535469#M7658</link>
      <description>&lt;P&gt;Hello,&lt;/P&gt;&lt;P&gt;I am looking at the Output in Results after running a Model Comaprison node for four models. I understand how lift/gain/%response is calculated across deciles but was wondering how these values are calculated for the 'whole' model (see below - apologies about formatting).&amp;nbsp;&lt;/P&gt;&lt;P&gt;Thanks,&lt;/P&gt;&lt;P&gt;Martin&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Data Role=Valid&lt;BR /&gt;&lt;BR /&gt;Statistics Reg Tree Neural Tree2&lt;BR /&gt;&lt;BR /&gt;Valid: Kolmogorov-Smirnov Statistic 0.41 0.37 0.42 0.37&lt;BR /&gt;Valid: Average Squared Error 0.12 0.12 0.13 0.13&lt;BR /&gt;Valid: Roc Index 0.76 0.72 0.77 0.72&lt;BR /&gt;Valid: Average Error Function 0.39 . 0.40 .&lt;BR /&gt;Valid: Bin-Based Two-Way Kolmogorov-Smirnov Probability Cutoff 0.13 0.10 0.17 0.22&lt;BR /&gt;Valid: Cumulative Percent Captured Response 27.43 27.54 21.71 21.26&lt;BR /&gt;Valid: Percent Captured Response 13.14 10.91 8.00 10.53&lt;BR /&gt;Valid: Divisor for VASE 2100.00 2100.00 2100.00 2100.00&lt;BR /&gt;Valid: Error Function 820.57 . 833.16 .&lt;BR /&gt;Valid: Gain 174.29 175.41 117.14 112.60&lt;BR /&gt;Valid: Gini Coefficient 0.52 0.43 0.53 0.43&lt;BR /&gt;Valid: Bin-Based Two-Way Kolmogorov-Smirnov Statistic 0.39 0.36 0.41 0.36&lt;BR /&gt;Valid: Kolmogorov-Smirnov Probability Cutoff 0.12 0.08 0.10 0.08&lt;BR /&gt;Valid: Cumulative Lift 2.74 2.75 2.17 2.13&lt;BR /&gt;Valid: Lift 2.65 2.20 1.62 2.13&lt;BR /&gt;Valid: Maximum Absolute Error 0.97 0.93 0.99 0.93&lt;BR /&gt;Valid: Misclassification Rate 0.17 0.16 0.17 0.17&lt;BR /&gt;Valid: Mean Squared Error 0.12 . 0.13 .&lt;BR /&gt;Valid: Sum of Frequencies 1050.00 1050.00 1050.00 1050.00&lt;BR /&gt;Valid: Root Average Squared Error 0.35 0.35 0.35 0.35&lt;BR /&gt;Valid: Cumulative Percent Response 45.71 45.90 36.19 35.43&lt;BR /&gt;Valid: Percent Response 44.23 36.70 26.92 35.43&lt;BR /&gt;Valid: Root Mean Squared Error 0.35 . 0.35 .&lt;BR /&gt;Valid: Sum of Squared Errors 256.65 261.89 263.95 264.27&lt;BR /&gt;Valid: Sum of Case Weights Times Freq 2100.00 . 2100.00 .&lt;BR /&gt;Valid: Number of Wrong Classifications . . 181.00 .&lt;/P&gt;</description>
      <pubDate>Thu, 14 Feb 2019 01:09:43 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Data-Science/Model-Comparison-Node-Lift-Value/m-p/535469#M7658</guid>
      <dc:creator>MartinBoland</dc:creator>
      <dc:date>2019-02-14T01:09:43Z</dc:date>
    </item>
    <item>
      <title>Re: Model Comparison Node - Lift Value</title>
      <link>https://communities.sas.com/t5/SAS-Data-Science/Model-Comparison-Node-Lift-Value/m-p/535599#M7659</link>
      <description>&lt;P&gt;Good question - it's not very clear in the output.&amp;nbsp; It's actually not for the whole model, but reporting the lift/gain-like statistics at depth 10 in the Statistics Comparison table.&lt;/P&gt;</description>
      <pubDate>Thu, 14 Feb 2019 14:24:03 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Data-Science/Model-Comparison-Node-Lift-Value/m-p/535599#M7659</guid>
      <dc:creator>WendyCzika</dc:creator>
      <dc:date>2019-02-14T14:24:03Z</dc:date>
    </item>
    <item>
      <title>Re: Model Comparison Node - Lift Value</title>
      <link>https://communities.sas.com/t5/SAS-Data-Science/Model-Comparison-Node-Lift-Value/m-p/535762#M7660</link>
      <description>Thanks Wendy. Have been reviewing Lift/Gain etc. for a certification exam. Your response was very helpful.</description>
      <pubDate>Thu, 14 Feb 2019 22:13:43 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Data-Science/Model-Comparison-Node-Lift-Value/m-p/535762#M7660</guid>
      <dc:creator>MartinBoland</dc:creator>
      <dc:date>2019-02-14T22:13:43Z</dc:date>
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