Comparison of several Regression techniques and Gaussian Process.

Examples taken from:

[1] MARTIN, OSVALDO. Bayesian Analysis with Python -: Implement Statistical Modeling and Probabilistic Programming Using pymc3. PACKT Publishing Limited, 2018.

• Linear regression
  • Robust linear regression
• Logistic regression
• Multivariate Linear and Logistic regression
• Poisson regression (ZIP)
• Polynomial regression (univariate and multivariate)
• Linear splines

• Gaussian Process Regression
• Regression with spatial autocorrelation
• Gaussian Process Classification
  • GP Classification with a More Complex Target
• Poisson Process (and Cox Process)

• Preprocessing
• Bayesian models
• Gaussian processes (potato)
• Gaussian processes (wheat)

. ├── data # Datasets used in notebooks ├── world # Geodata for plotting world maps ├── 1.* ... 5.*.ipynb # Notebooks ├── guassian_processes.py # GP utility class ├── utils.py # Utility functions ├── LICENSE └── README.md 

Recommended to create a venv; recommended to install pymc separatly with conda if on windows (Instructions);

then:

pip install -r requirements.txt 

Just use them as a regular ipy notebooks