{"title":"PCA","nodeType":"Manipulator","id":"*-BB0l1REE9I_B16p","factoryName":"org.knime.base.node.mine.transformation.pca.perform.PCA2NodeFactory","factoryId":"org.knime.base.node.mine.transformation.pca.perform.PCA2NodeFactory","path":["Analytics","Mining","PCA"],"owner":"knime","ownerAccountId":"account:team:b5f0848f-496d-4e6a-b869-fa3532248db7","description":"<p>This node performs a <a href=\"http://en.wikipedia.org/wiki/Principal_component_analysis\" rel=\"ugc nofollow noopener noreferrer\"> principal component analysis (PCA)</a> on the given data. The input data is projected from its original feature space into a space of (possibly) lower dimension with a minimum of information loss.</p>\n        ","shortDescription":"Principal component analysis","keywords":["principal component analysis"],"deprecated":false,"streamable":false,"tags":["Analytics","Mining","PCA"],"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 data for the PCA"}],"outPorts":[{"objectClass":"org.knime.core.node.BufferedDataTable","color":"000000","dataType":"Table","optional":false,"name":"Transformed data","description":"Table with input values projected to their principal components"}],"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":"Select the number of dimensions the input data is projected to.\n<ul><li><b>Dimension(s) to reduce to</b> : Select a fixed number of target dimensions. It must be lower than or equal to the number of input columns.</li><li><b>Minimum information fraction</b> : Specify the minimal amount of information to be preserved.</li></ul>","optional":false},{"name":"Number of dimensions","description":"The number of dimensions to reduce the data to.","optional":false},{"name":"Information preservation (%)","description":"The minimum percentage of information to preserve in the reduced dimensions.","optional":false},{"name":"Columns","description":"Select the columns that are included by the PCA, i.e the original features.","optional":false},{"name":"Remove original data columns","description":"If checked, the columns containing the input data are removed.","optional":false},{"name":"Fail if missing values are encountered","description":"If checked, execution fails, when the selected columns contain missing values. By default, rows containing missing values are ignored and not considered during the computation.","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":[]}