Some new free nodes provided by Lhasa Limited are now available from the trusted community update site (https://tech.knime.org/lhasa-nodes-for-knime).
Nodes:
Discretise: Performs a very simple discretisation based on the value falling below a set value. If the boundary is set to 2 all values in the selected column(s) below 2 will be set to 0 and all values equal to or greater than 2 will be set to 1.
Binary scorer: Takes an input containing an activity (experimental/true) and multiple (or one) prediction columns. For multi class classifications you should use the KNIME Scorer node. This node has been developed for binary classification and you must specify the value of active (positive) and inactive (negative). Values can be specified for equivocal and out of domain regardless of whether they are present in the prediction column.
Binned performance: Calculates various performance measures like the binary scorer. This node will take a numeric column (compatible with DoubleValue) and allow binning on this column. Example usage to assess the model performance for different confidence ranges.
Result: Returns an additional column with the values: true positive, true negative, false positive, false negative for a binary classification problem. Specify the active string using the text entry, default is active.
Dumb Joiner: Appends the columns from table 2 to table 1. Checks to make sure the tables have the same number of columns but they must already be sorted. Unlike the column appender this node does not check that the RowID's are equal.
Row Splitter (col+): The RowFilter node has been adapted to allow for multiple column selection to perform the attribute matching (include and exclude). It is possible to match based on a single column match (only one must return true) or every column match (all must return true). This can be used to identify rows where any or all columns have a particular value.
More details available here: https://tech.knime.org/lhasa-nodes-for-knime
Cheers
Sam