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Loan_​Data_​Analysis

Loan Data Analysis

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.

Node 1Node 2Node 3Node 4Node 5Node 6Node 7Node 8Node 9Node 10Node 11CSV Reader Partitioning DecisionTree Learner Decision TreePredictor Scorer Scorer Random ForestLearner Random ForestPredictor Naive Bayes Learner Naive BayesPredictor Scorer Node 1Node 2Node 3Node 4Node 5Node 6Node 7Node 8Node 9Node 10Node 11CSV Reader Partitioning DecisionTree Learner Decision TreePredictor Scorer Scorer Random ForestLearner Random ForestPredictor Naive Bayes Learner Naive BayesPredictor Scorer

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