ModelPredictedLabelConfig: ModelPredictedLabelConfig Class

In DyfanJones/sagemaker-r-common: R6sagemaker lower level api calls

ModelPredictedLabelConfig Class

Description

Config object to extract a predicted label from the model output.

Public fields

label

Predicted label of the same type as the label in the dataset

probability

Optional index or JSONPath location in the model

probability_threshold

An optional value for binary prediction task

predictor_config

Predictor dictionary of the analysis config.

Methods

Public methods

• ModelPredictedLabelConfig$new()

• ModelPredictedLabelConfig$get_predictor_config()

• ModelPredictedLabelConfig$format()

• ModelPredictedLabelConfig$clone()

---

Method new()

Initializes a model output config to extract the predicted label. The following examples show different parameter configurations depending on the endpoint:

• Regression Task: The model returns the score, e.g. 1.2. we don't need to specify anything. For json output, e.g. list('score'=1.2) we can set ''label='score”'

• Binary classification:

• The model returns a single probability and we would like to classify as 'yes' those with a probability exceeding 0.2. We can set ''probability_threshold=0.2, label_headers='yes”'.

• The model returns list('probability'=0.3), for which we would like to apply a threshold of 0.5 to obtain a predicted label in list(0, 1). In this case we can set ''label='probability”'.

• The model returns a tuple of the predicted label and the probability. In this case we can set ''label=0''.

• Multiclass classification:

• The model returns list('labels'= c('cat', 'dog', 'fish'), 'probabilities'=c(0.35, 0.25, 0.4)). In this case we would set the ''probability='probabilities”' and ''label='labels”‘ and infer the predicted label to be '’fish.''

• The model returns list('predicted_label'='fish', 'probabilities'=c(0.35, 0.25, 0.4])). In this case we would set the ''label='predicted_label”'.

• The model returns c(0.35, 0.25, 0.4). In this case, we can set ''label_headers=['cat','dog','fish']'‘ and infer the predicted label to be '’fish.''

Usage

ModelPredictedLabelConfig$new(
  label = NULL,
  probability = NULL,
  probability_threshold = NULL,
  label_headers = NULL
)

Arguments

label

(str or [integer] or list[integer]): Optional index or JSONPath location in the model output for the prediction. In case, this is a predicted label of the same type as the label in the dataset no further arguments need to be specified.

probability

(str or [integer] or list[integer]): Optional index or JSONPath location in the model output for the predicted scores.

probability_threshold

(float): An optional value for binary prediction tasks in which the model returns a probability, to indicate the threshold to convert the prediction to a boolean value. Default is 0.5.

label_headers

(list): List of label values - one for each score of the “probability“.

---

Method get_predictor_config()

Returns probability_threshold, predictor config.

Usage

ModelPredictedLabelConfig$get_predictor_config()

---

Method format()

format class

Usage

ModelPredictedLabelConfig$format()

---

Method clone()

The objects of this class are cloneable with this method.

Usage

ModelPredictedLabelConfig$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

DyfanJones/sagemaker-r-common documentation built on June 14, 2022, 10:31 p.m.