<s>[INST] using logistic regression, decision trees, or other types of regression models, name at least 2 prediction techniques that yield good kaggle performance
Among the methods listed in your book, "Python Machine Learning" by " Raschka & Mirjalili" , which of those do you think also would give good results (be it by its performance, accuracy or running time) assuming moderately sized data fits in memory but 
- handling high-cardinality categorical variables (>100 distinct), 
- non linear features, 
- missing values and 
- good interpretability?[/INST]