[R] Flexibility and Interpretability

1. Parametric and Non-Parametric Methods 

• Parametric methods : Make an assumption about the functional form or shape of \(f\). 
• Non-Parametric methods : Do not make explicit assumptions about the functional form of \(f\). 
  
  

2. Flexibility and Interpretability

• Flexibility : The flexibility of a model can be described as how much is model's behavior influenced by characteristics of the data. 
• So, if flexibility increase when we increase df(degree of freedom or model complexity). 
• Less flexible(Restricitve) models have more interpritability. 
• Considering only prediction, the most flexible model is prefable. 

In other words, flexibility and interpretability are cross-relationships, and the analysis of parameters and the model's predictive performance are selected according to the importance.