# MACHINE_LEARNING

Machine learning section [Edit on GitHub]

Subsections

- TRAINING_SET

## Keywords

- DESCRIPTOR

- GP_NOISE_VAR

- GP_SCALE

- METHOD

- PRIOR

- TOLERANCE

## Keyword descriptions

DESCRIPTOR: enum = POTENTIAL

  Valid values:

  - `POTENTIAL` Eigenvalues of local potential matrix

  - `OVERLAP` Eigenvalues of local overlap matrix

  - `R12` Distance between two atoms (just for testing)

  References: Zhu2016

  Descriptor used as input for machine learning. [Edit on GitHub]

GP_NOISE_VAR: real = 1.00000000E-001

  Variance of noise used for Gaussian Process machine learning. [Edit on GitHub]

GP_SCALE: real = 5.00000000E-002

  Mentions: ⭐PAO-ML

  Length scale used for Gaussian Process machine learning. [Edit on GitHub]

METHOD: enum = GAUSSIAN_PROCESS

  Valid values:

  - `GAUSSIAN_PROCESS` Gaussian Process

  - `NEURAL_NETWORK` Neural Network

  - `LAZY` Just rely on prior

  Machine learning scheme used to predict PAO basis sets. [Edit on GitHub]

PRIOR: enum = ZERO

  Valid values:

  - `ZERO` Simply use zero

  - `MEAN` Use average of training-set

  Prior used for predictions. [Edit on GitHub]

TOLERANCE: real = 1.00000000E-002

  Maximum variance tolerated when making predictions. [Edit on GitHub]