Running this sample on the same KNIME version on a colleagues computer works fine. I have started KNIME already mit -clean, nothing helps. Requirements: - KNIME Analytics Platform + KNIME Extension for Apache Spark. It also demonstrates the conversion of categorical columns into numerical columns which is necessary since the MLlib algorithms only support numerical features and labels. I think KNIME has some kind of state in this node, at least obviously in the eclipse workspace for sure. This workflow demonstrates the usage of the Spark MLlib Decision Tree Learner and Spark Predictor. Replaces cells in a column according to dictionary table (. When I came back it did not work anymore. Drag & drop this node right into the Workflow Editor of KNIME Analytics Platform (4.x or higher).
I changed basically the XMX setting in KNIME.ini, restarted KNIME and have run several other workflows. I have to say, yesterday this has worked. The warning being shown is just about the possible problem with reusing the KNIME node in a machine learning context as with R oder Spark/MLLIB because if model incompatibility problems. WARN Missing Value 2:2 The current settings use missing >value handling methods that cannot be represented in PMML 4.2
The sample workflow is primitive and looks like:Ĭonfig of the first node which reads the excel file (XLSX)Ĭonfig of the second node, which should replace the missing values: But my current problem is rather simple, I am in a 'data preparation step' where the missing value node in KNIME does not work. It is about ecommmerce transactions where a association rule analysis should be done later. From the dictionary table, choose one column (or the rowID column) that is used as lookup criterion. The node has two inputs: The first input contains a target column whose values are to be replaced using the dictionary table (2nd input). I'm running KNIME to prepare some ML data sets. Replaces cells in a column according to dictionary table (2nd input).