Model Visualisation
Model Visualisation
With Python and R Code
Though visualisation is used in data science to understand the shape of the data (data-vis), it is not widely used for the models developed; which are largely evaluated based on numerical summaries. Model visualisation (model-vis) can help understand: the shape of the model, the impact of parameters & different input data on the model, the fit of the model & where it can be improved.
1. Introduction
2. Learning and Layers
3. n/p/N Challenge
4. Regression: Small
(p = 10, n < 1K)
5. Regression: N Models
(p = 10, n < 10K, model = 50)
6. Classification: 2 Class
(p = 10, n < 100K, class = 2)
7. Classification: 10 Class
(p = 10, n < 100K, class = 10)
8. Classification: Large
(p = 10, n ~ 1M)