KNIME Data Science Learnathon - Group 2A - Training Evaluation and Optimization

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Solution to the tasks for Group 2 in KNIME Data Science Learnathon
- Train a Decision Tree on the training set, and apply the model to the test set
- Evaluate the performance of the Decision Tree model
- Train a Logistic Regression model on the training set, and apply the model to the test set
- Evaluate the performance of the Logistic Regression model
- Optimize the tree depth of a Random Forest model, and train and apply a Random Forest model using the optimal parameter value
- Evaluate the performance of the Random Forest model
- Compare the performances of the different models using scoring metrics for a classification model and an ROC Curve
- Write the best performing model to a file

URL: Import Existing Models - KNIME Blog https://www.knime.com/blog/pmml-integration-in-knime
URL: KNIME Learning Center - KNIME.com https://www.knime.com/learning
URL: From Modeling to Scoring: Confusion Matrix and Class Statistics - KNIME Blog https://www.knime.com/blog/from-modeling-to-scoring-confusion-matrix-and-class-statistics
URL: KNIME Cheat Sheets - KNIME.com https://www.knime.com/cheat-sheets

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