The following node is available in the Open Source KNIME predictive analytics and data mining platform version 2.7.1. Discover over 1000 other nodes, as well as enterprise functionality at http://knime.com.
Performs a multinomial logistic regression. Select in the dialog a
target column (combo box on top), i.e. the response. The two
lists in the center of the dialog allow you to include only certain
columns which represent the (independent) variables.
Make sure the columns you want to have included being in the right
"include" list.
See article in wikipedia about
logistic regression
for an overview about the topic.
This particular implementation uses an iterative optimization procedure
termed Fisher's scoring in order to compute the model.
If the optional PMML inport is connected and contains
preprocessing operations in the TransformationDictionary those are
added to the learned model.
0 | Table on which to perform regression. The input must not contain missing values, you have to fix them by e.g. using the Missing Values node. |
1 | Optional PMML port object containing preprocessing operations. |
0 | Model to connect to a predictor node. |
1 | Coefficients and statistics of the logistic regression model. |