{"title":"Numeric Scorer","nodeType":"Other","id":"*ZqcMbr00jkoQ1av4","factoryName":"org.knime.base.node.mine.scorer.numeric2.NumericScorer2NodeFactory","factoryId":"org.knime.base.node.mine.scorer.numeric2.NumericScorer2NodeFactory","path":["Analytics","Mining","Scoring"],"owner":"knime","ownerAccountId":"account:team:b5f0848f-496d-4e6a-b869-fa3532248db7","description":"<p>This node computes certain statistics between the a numeric column&#39;s values (r <sub>i</sub> ) and predicted (p <sub>i</sub> ) values. It computes <a href=\"http://en.wikipedia.org/wiki/Coefficient_of_determination\" rel=\"ugc nofollow noopener noreferrer\">R²</a> &#61;1-SS <sub>res</sub> /SS <sub>tot </sub> &#61;1-Σ(p <sub>i</sub> -r <sub>i</sub> )²/Σ(r <sub>i</sub> -1/n*Σr <sub>i</sub> )² (can be negative!), <a href=\"http://en.wikipedia.org/wiki/Mean_absolute_error\" rel=\"ugc nofollow noopener noreferrer\">Mean absolute error</a> (1/n*Σ|p <sub>i</sub> -r <sub>i</sub> |), <a href=\"http://en.wikipedia.org/wiki/Residual_sum_of_squares\" rel=\"ugc nofollow noopener noreferrer\">Mean squared error</a> (1/n*Σ(p <sub>i</sub> -r <sub>i</sub> )²), <a href=\"http://en.wikipedia.org/wiki/Root-mean-square_deviation\" rel=\"ugc nofollow noopener noreferrer\">Root mean squared error</a> (sqrt(1/n*Σ(p <sub>i</sub> -r <sub>i</sub> )²)), <a href=\"http://en.wikipedia.org/wiki/Mean_signed_difference\" rel=\"ugc nofollow noopener noreferrer\">Mean signed difference</a> (1/n*Σ(p <sub>i</sub> -r <sub>i</sub> )), <a href=\"https://en.wikipedia.org/wiki/Mean_absolute_percentage_error\" rel=\"ugc nofollow noopener noreferrer\">Mean absolute percentage error</a> 1/n * Σ((|r <sub>i</sub> - p <sub>i</sub> |)/ |r <sub>i</sub> |), <a href=\"https://en.wikipedia.org/wiki/Coefficient_of_determination#Adjusted_R2\" rel=\"ugc nofollow noopener noreferrer\">Adjusted R²</a> &#61;1-(1-R²)(n-1)/(n-p-1) (can be negative!). The computed values can be inspected in the node&#39;s view and/or further processed using the output table.</p>\n        ","shortDescription":"Computes certain statistics between the a numeric column's values and predicted values.","keywords":[],"deprecated":false,"streamable":false,"tags":["Analytics","Mining","Scoring"],"icon":"data:image/png;base64,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","views":[{"name":"Statistics","description":"A table with the statistical measures"}],"inPorts":[{"objectClass":"org.knime.core.node.BufferedDataTable","color":"000000","dataType":"Table","optional":false,"name":"Table","description":"Table with predicted and reference numerical data."}],"outPorts":[{"objectClass":"org.knime.core.node.BufferedDataTable","color":"000000","dataType":"Table","optional":false,"name":"Statistics","description":"The computed statistical measures:\n<ul><li>R² - <a href=\"http://en.wikipedia.org/wiki/Coefficient_of_determination\" rel=\"ugc nofollow noopener noreferrer\">coefficient of determination</a> , 1-SS_res/SS_tot</li><li><a href=\"http://en.wikipedia.org/wiki/Residual_sum_of_squares\" rel=\"ugc nofollow noopener noreferrer\">Mean squared error</a> - 1/n*Σ((p_i-r_i)²)</li><li><a href=\"http://en.wikipedia.org/wiki/Mean_absolute_error\" rel=\"ugc nofollow noopener noreferrer\">Mean absolute error</a> - 1/n*Σ|p_i-r_i|</li><li><a href=\"http://en.wikipedia.org/wiki/Root-mean-square_deviation\" rel=\"ugc nofollow noopener noreferrer\">Root mean squared error</a> - Sqrt(1/n*Σ((p_i-r_i)²))</li><li><a href=\"http://en.wikipedia.org/wiki/Mean_signed_difference\" rel=\"ugc nofollow noopener noreferrer\">Mean signed difference</a> - 1/n*Σ(p_i - r_i)</li><li><a href=\"https://en.wikipedia.org/wiki/Mean_absolute_percentage_error\" rel=\"ugc nofollow noopener noreferrer\">Mean absolute percentage error</a> 1/n * Σ((|r_i - p_i|)/|r_i|)</li><li><a href=\"https://en.wikipedia.org/wiki/Coefficient_of_determination#Adjusted_R2\" rel=\"ugc nofollow noopener noreferrer\">Adjusted R²</a> 1-(1-R²)(n-1)/(n-p-1)</li></ul>"}],"dynInPorts":[],"dynOutPorts":[],"additionalSiteInformation":{"url":"https://update.knime.com/analytics-platform/5.12","trusted":true,"enabledByDefault":true,"name":"KNIME Analytics Platform 5.12 Update Site","version":"5.12.0"},"dialog":[{"sectionName":"Options","fields":[{"name":"Reference column","description":"Column with the correct, observed, training data values.","optional":false},{"name":"Predicted column","description":"Column with the modeled, predicted data values.","optional":false},{"name":"Override output column name","description":"Overrides the name of the column in the output. By default, the name of the predicted column is used.","optional":false},{"name":"Output column name","description":"The name of the column in the output.","optional":false},{"name":"Export and prefix flow variables","description":"If enabled, the scores will be exported as flow variables with hard coded names and prefixed by the given value.","optional":false},{"name":"Number of predictors","description":"The number of predictors used to compute the adjusted R squared. The adjusted R squared is calculated as: 1 - ((1 - R²) * (n - 1)) / (n - p - 1), where n is the number of observations and p is the number of predictors.","optional":false}]}],"links":[],"kudos":[],"kudosCount":0,"bundleInformation":{"bundleVersion":"5.12.0.v202606261225","bundleName":"KNIME Base Nodes","bundleSymbolicName":"org.knime.base","bundleVendor":"KNIME AG, Zurich, Switzerland","featureSymbolicName":"org.knime.features.base","featureName":"KNIME Base nodes","featureVersion":"5.12.0.v202606261225","featureVendor":"KNIME AG, Zurich, Switzerland","extensionId":"*bjR3r1yWOznPIEXS"},"frequentSuccessors":[]}