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Class representing a PetroVisor ml model object.

Public fields

name

The name of the ml model.

modelType

The model's type.

trainedModel

This field holds the string representation of the trained ML model.

tableFormula

The model's table formula as string.

contextFormula

The model's context formula as string.

labelColumnName

The model's label column name.

isLocked

This flag specifies whether the model is locked. Defaults to FALSE.

user

The user the model belongs to.

isFavorite

This flag specifies whether the model is marked as favorite item, and thus shown in the favorites tab on the home module in PetroVisor. Defaults to FALSE.

labels

A list of strings holding the labels of the model.

Methods


Method new()

Create a new ML model instance.

Usage

MLModel$new(
  name = NULL,
  modelType = NULL,
  trainedModel = NULL,
  tableFormula = NULL,
  contextFormula = NULL,
  labelColumnName = NULL,
  isLocked = FALSE,
  user = NULL,
  isFavorite = FALSE,
  labels = NULL
)

Arguments

name

The name of the ml model.

modelType

The model's type.

trainedModel

This field holds the string representation of the trained ML model.

tableFormula

The model's table formula as string.

contextFormula

The model's context formula as string.

labelColumnName

The model's label column name.

isLocked

This flag specifies whether the model is locked. Defaults to FALSE.

user

The user the model belongs to.

isFavorite

This flag specifies whether the model is marked as favorite item, and thus shown in the favorites tab on the home module in PetroVisor. Defaults to FALSE.

labels

A list of strings holding the labels of the model.


Method toList()

Usage

MLModel$toList()

Details

Convert the object to a list. This function is mainly used by the RepositoryService to convert the objects to lists and then call the web API.


Method clone()

The objects of this class are cloneable with this method.

Usage

MLModel$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Examples

if (FALSE) { # \dontrun{
MLModel$new()
} # }