Numeric Scorer gives a negative R^2 (R-squared)

[mlauber71]

@RichardFL

1- I see that me using two separate files, one for training and one for testing doesn’t work. How come? isn’t this the standard.?

The question is what is your target variable. From the structure of you data it seemed your second dataset was the one with the unknown target data. You would have to define which column you want to predict. Then you would split your original data into test and training. If your testate does not contain the target variables you will not be able to test the quality of your model.

@RichardFL

2- If I merge my training data with my testing data and use the Partitioning Node , how can I ensure that Knime knows which data is which? My testing file does not have the column with data I need to predict (Item_outlet_sales) column, How do I make sure Knime does not try to use this to train the model?

If you use the Partitioning node you have two Streams of data. You tell them apart by connecting the training nodes to the upper arrow and the testing/predicting nodes to the lower part.

The modification of your workflow I uploaded renames your value to “Target”.

It might be useful to familiarise yourself with the concepts of predicting with a basic example, where you can still read the rules that are generated:

Looking for options to evaluate a decision tree

One ‘brutal’ way could be to convert the decision tree rules into SQL and then use the SQL code. Or use the ruleset to make some kind of If then rules. Not very elegant I have to admit. [27] [35] kn_example_decision_tree.knwf (510.8 KB)