Random seed in Knime partitioning node is “1639924778212” set by default in my case. When changing the seed number to “42”, which is normally used in train_test_split in sk-learn, the regression result is quite different. it becomes worse in my case.
Q1: how the seed number is set by default?
Q2. why the difference can be so big when change the seed number to 42?