{"title":"Feature Selection Filter","nodeType":"Manipulator","id":"*IfVMh6WXpGwR09zy","factoryName":"org.knime.base.node.meta.feature.selection.FeatureSelectionFilterNodeFactory","factoryId":"org.knime.base.node.meta.feature.selection.FeatureSelectionFilterNodeFactory","path":["Analytics","Mining","Feature Selection"],"owner":"knime","ownerAccountId":"account:team:b5f0848f-496d-4e6a-b869-fa3532248db7","description":"<p>This node takes a model built with a feature selection loop as input and lets you choose the subset of columns you want to include in the output table. The dialog shows all computed subsets together with their scores. You can select a subset manually or specify a score threshold. If you specify a threshold, the smallest feature set whose score meets the threshold requirement is selected. If the &#34;Minimize Score&#34; option was checked in the Feature Selection Loop End node, this is the smallest feature set with a score below the specified threshold; if the &#34;Minimize Score&#34; option was left unchecked in the Feature Selection Loop End node, this is the smallest feature set with a score above the specified threshold.</p>\n        ","shortDescription":"Applies a feature filter model built during feature selection.","keywords":[],"deprecated":false,"streamable":false,"tags":["Analytics","Mining","Feature Selection"],"icon":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABAAAAAQCAYAAAAf8/9hAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAAN1wAADdcBQiibeAAAABl0RVh0U29mdHdhcmUAd3d3Lmlua3NjYXBlLm9yZ5vuPBoAAADxSURBVDiNY/z//z8DMmBkZBRkYGD4/f///y8MRAAmLGLqDAwMtxgZGQsZGRkZCRnAyMDAwDI73vA3zCV3X33707nj1h9WZkYOBWHu/7nOSn+M5QW+WbUfFOgqO/0DWXNZlykHCwMDg2XFmqsMMI/8/vePmYGBgfn33/8Md19/YWzafIN1apQ+J1SaHd0FLP///z98rNIeLnDl6ac/6Ysv/BHjZee0UxNmyHJUYmBnYfqPrhFuALoAEyPDfwYGhuOz4w2dRHjYCAUBZiBqSfH9////vzMxmrEaQCoYNWAwGABLSD+RxH5gU4gLMKJnZ1IBANfKSfqlUghnAAAAAElFTkSuQmCC","views":[],"inPorts":[{"objectClass":"org.knime.base.node.meta.feature.selection.FeatureSelectionModel","color":"9b9b9b","dataType":"Feature Selection Model","optional":false,"name":"Selection model","description":"A feature selection model."},{"objectClass":"org.knime.core.node.BufferedDataTable","color":"000000","dataType":"Table","optional":false,"name":"Any datatable","description":"Any data table that should contain the same columns as used in the selection loop."}],"outPorts":[{"objectClass":"org.knime.core.node.BufferedDataTable","color":"000000","dataType":"Table","optional":false,"name":"Filtered table","description":"The input table with some columns filtered out."}],"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":"Feature set selection mode","description":"Choose how the features are selected from the available feature sets computed during the feature selection loop.\n<ul><li><b>Manual</b> : Choose a set of features to include.</li><li><b>Best score</b> : The feature set with the best prediction score is chosen. If the score is being maximized, the best score is the highest score value; if the score is being minimized, the best score is the lowest score value.</li><li><b>Threshold</b> : Set a prediction score threshold. The smallest feature set whose score meets the threshold requirement is selected: below the threshold if the score is minimized, above the threshold if the score is maximized.</li></ul>","optional":false},{"name":"Select a feature set","description":"Select the feature set based on the score and number of features.","optional":false},{"name":"Prediction score threshold","description":"Enter a prediction score threshold here. The smallest feature set whose score meets the threshold requirement is selected.","optional":false},{"name":"Include static columns","description":"If checked, any static columns (columns that were not part of the feature selection, i.e. constant columns kept throughout the selection loop) are included in the output table. Otherwise, they are filtered out.","optional":false},{"name":"Included features","description":"This shows the columns that are included in the output table. The list is automatically updated based on the selection configuration and whether static columns are included.","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":[{"id":"*T0AhxSe0Yi42rQK8","factoryName":"org.knime.base.node.preproc.partition.PartitionNodeFactory","probability":0.1518987341772152},{"id":"*ZgYyOm1P9VJVBE9e","factoryName":"org.knime.base.node.preproc.joiner.Joiner2NodeFactory","probability":0.08860759493670886},{"id":"*BKpS2Ow-rnvw2TSf","factoryName":"org.knime.base.node.meta.xvalidation.XValidatePartitionerFactory","probability":0.05063291139240506},{"id":"*laI6npAqSiKLMn5S","factoryName":"org.knime.base.node.preproc.split2.SplitNodeFactory2","probability":0.05063291139240506},{"id":"*2hhbyPN8yXaMD1YU","factoryName":"org.knime.base.node.mine.treeensemble2.node.randomforest.learner.classification.RandomForestClassificationLearnerNodeFactory2","probability":0.0379746835443038},{"id":"*g9kQ4icd1YZR9cjQ","factoryName":"org.knime.ext.h2o.nodes.table2frame.H2OTableToFrameNodeFactory","probability":0.0379746835443038},{"id":"*_zMUh-EpYjdvFKW9","factoryName":"org.knime.base.node.preproc.columnappend.ColumnAppenderNodeFactory","probability":0.0379746835443038},{"id":"*DOkyMaii62U05xZ1","factoryName":"org.knime.base.node.preproc.filter.column.DataColumnSpecFilterNodeFactory","probability":0.0379746835443038},{"id":"*mTvdLptC3aqDqGrI","factoryName":"org.knime.base.node.mine.decisiontree2.predictor2.DecTreePredictorNodeFactory","probability":0.02531645569620253},{"id":"*izly7J6Cf2Jpbfso","factoryName":"org.knime.base.node.mine.treeensemble2.node.randomforest.predictor.classification.RandomForestClassificationPredictorNodeFactory2","probability":0.02531645569620253}]}