{"title":"Linear Discriminant Analysis","nodeType":"Manipulator","id":"*ibfEoz796QwX_D58","factoryName":"org.knime.base.node.stats.transformation.lda2.perform.LDA2NodeFactory","factoryId":"org.knime.base.node.stats.transformation.lda2.perform.LDA2NodeFactory","path":["Analytics","Mining","Linear Discriminant Analysis"],"owner":"knime","ownerAccountId":"account:team:b5f0848f-496d-4e6a-b869-fa3532248db7","description":"<p>This node performs <a href=\"http://en.wikipedia.org/wiki/Linear_discriminant_analysis\" rel=\"ugc nofollow noopener noreferrer\">Linear Discriminant Analysis (LDA)</a> which is a dimensionality reduction technique. It takes class information into account in order to project the data into a space in which classes are well separated. The results are similar to <a href=\"https://en.wikipedia.org/wiki/Principal_component_analysis\" rel=\"ugc nofollow noopener noreferrer\">Principle Component Analysis (PCA)</a> and may be used in subsequent classification.</p><p>This node is equivalent to using a <i>Linear Discriminant Ananlysis Compute</i> node in combination with a <i>Linear Discriminant Analysis Apply</i> node. This pattern may be useful when applying a transformation to multiple datasets.</p>\n            \n        \n        ","shortDescription":"This node performs a linear discriminant analysis.","keywords":[],"deprecated":false,"streamable":false,"tags":["Analytics","Mining","Linear Discriminant Analysis"],"icon":"data:image/png;base64,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","views":[],"inPorts":[{"objectClass":"org.knime.core.node.BufferedDataTable","color":"000000","dataType":"Table","optional":false,"name":"Table to transform","description":"Input table containing numeric columns and one column with class information."}],"outPorts":[{"objectClass":"org.knime.core.node.BufferedDataTable","color":"000000","dataType":"Table","optional":false,"name":"Transformed data","description":"The original data (if not excluded) plus columns for the projected dimensions."}],"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":"Target dimensions","description":"Number of dimensions to reduce the input data to. This cannot exceed the number of classes minus one or the number of selected columns, depending on which one is smaller.","optional":false},{"name":"Class column","description":"Column containing class information.","optional":false},{"name":"Column selection","description":"Columns containing the input data.","optional":false},{"name":"Remove original data columns","description":"If checked, the columns containing the input data are removed from the output table.","optional":false},{"name":"Fail if missing values are encountered","description":"If checked, execution fails when the selected columns contain missing values. Otherwise, rows containing missing values are ignored during computation.","optional":false}]}],"links":[],"kudos":[],"kudosCount":0,"bundleInformation":{"bundleVersion":"5.12.0.v202604281126","bundleName":"KNIME Statistic Nodes","bundleSymbolicName":"org.knime.stats","bundleVendor":"KNIME AG, Zurich, Switzerland","featureSymbolicName":"org.knime.features.stats","featureName":"KNIME Statistics Nodes","featureVersion":"5.12.0.v202604281126","featureVendor":"KNIME AG, Zurich, Switzerland","extensionId":"*G7WNikjPW2P03gXm"},"frequentSuccessors":[]}
