kn_example_rose_balanced
Use SMOTE and ROSE algorithms to balance data
Use both SMOTE (Synthetic Minority Over-sampling Technique) and ROSE (Random Over-Sampling Examples) algorithms to balance data. SMOTE is implemented within KNIME. ROSE can be accessed via R.
It is advisable to balace only your training data and leave the test/validation data as they are or you run the risk of greatly inflated values on your precision statistics.
Nodes
Extensions
Links
- R ROSEwww.rdocumentation.org/packages/ROSE
- forum entryforum.knime.com/t/smote-more-efficient-way-for-oversampling/17769/2?u=mlauber71
- How to handle Imbalanced Classification Problemswww.analyticsvidhya.com/blog/2017/03/imbalanced-data-classification/
- SMOTE Hints from KNIME Team members 1forum.knime.com/t/how-to-deal-with-unbalanced-data-smote-vs-equalizer/9358/2?u=mlauber71
- SMOTE Hints from KNIME Team members 2forum.knime.com/t/smote-for-unbalanced-data/10274/2?u=mlauber71
- SMOTE Hints from KNIME Team members 3 (Classification Threshold Analysis)forum.knime.com/t/optimization-options/17794/3?u=mlauber71
- more options about unbalanced dataforum.knime.com/t/xgboost-predictor/23960/5?u=mlauber71