Final Exercise
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Decision Tree - exercise
Introduction to Machine Learning Algorithms course - Session 1
Exercise 1
- Partition data into training and test set
- Train a decision rree model
- Apply the model to the test set
- Evaluate the model performance
URL: Description of the Ames Iowa Housing Data https://rdrr.io/cran/AmesHousing/man/ames_raw.html
URL: Ames Housing Dataset on kaggle https://www.kaggle.com/prevek18/ames-housing-dataset
URL: Decision Tree https://www.youtube.com/watch?v=CSwM92yTrJw
URL: Behind the scenes of Decision Tree https://www.youtube.com/watch?v=qB8HZpwqPEg
URL: Slides (Introduction to ML Algorithms course) https://www.knime.com/form/material-download-registration
Nodes
- Decision Tree Learner2 ×
- Decision Tree Predictor2 ×
- Scorer2 ×
- Binary Classification Inspector1 ×
- CSV Reader1 ×
- Column Filter1 ×
- Parameter Optimization Loop End1 ×
- Parameter Optimization Loop Start1 ×
- Partitioning1 ×
- ROC Curve1 ×
- Random Forest Learner1 ×
- Random Forest Predictor1 ×
- Rule Engine1 ×
Extensions
- FeatureKNIME Base nodes
- FeatureKNIME Ensemble Learning Wrappers
- FeatureKNIME Javasnippet
- FeatureKNIME Machine Learning Interpretability Extension
- FeatureKNIME Optimization extension
- Show all 6 modules
Links
- No links available