Terms to Learn

This chapter and the Glossary at the end of the text contain definitions of the following important terms:

1. confusion matrix
2. cross-validation
3. data science
4. decision tree
5. false negatives (FN)
6. false positive rate
7. false positives (FP)
8. Gini impurity
9. hyperparameter
10. overfitting
11. predictive modeling
12. pruning
13. receiver operating characteristic (ROC) curve
14. target leakage
15. true positive rate
16. true positives (TP)
17. true negatives (TN)