Machine Learning Techniques have been used to investigate the prediction of loans being full paid or not. The KNIME analytics platform has been used to demonstrate the utilisation of visual programming in achieving this task.
- a Random Forest Classifier has been used and the accuracy for this model is 84.2%
- a Decision Tree Classifier has been used and the accuracy for this model is 84.3%
- a Naive Bayes Classifier has been used and the accuracy for this model is 84.2%
- All three applied models show nearly identical accuracy.
To use this workflow in KNIME, download it from the below URL and open it in KNIME:
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