Mindmap
Algorithms
Inhalt der Mindmap
Algorithms
Penalized Regression
- Common Usage
- Supervised regression
- Supervised Classification
- Common Concerns
- Missing Values
- Outliers
- Standardization
- Parameter tuning
- Suggested Scale
- Small to large data
- Suggested Usage
- Modeling linear or linearly separable phenomena
- Manually specifying nonlinear and explicit interaction terms
- Well suited for N << p
- Interpretability
- HIGH
- Common Usage
Naïve Bayes
Informationen
- Beschreibung
- Mindmap am Algorithms, erstellt von chema arce am 07/07/2017.
- Erstellt von
- chema arce
- Aufrufe
- 1
- Bewertung