Before hiring me, you can discover my pros and cons and when I work best from Table 3 so that you don't have any late regrets!
| Agent | Pros | Cons | Better at |
| Decision trees (DTs) |
-Simple to implement, train, and interpret -Trees can be visualized -Requires little data preparation -Less model building and prediction time -Can handle both numeric and categorical data -Possible of validating the model using the statistical tests -Robust against noise and missing values -High accuracy |
-Interpretation is hard with large and complex trees -Duplication may occur within the same subtree -Possible issues with diagonal decision boundaries -DT learners can create overcomplex trees that do not generalize data well -Sometimes DTs can be unstable because of small variants in the data -Learning the DTs itself an NP-complete problem (aka. nondeterministic polynomial time -complete problem) -DTs learners create biased trees if some classes dominate |
-Targeting highly accurate classification -Medical diagnosis and prognosis -Credit risk analytics |