26 lines
1.7 KiB
YAML
26 lines
1.7 KiB
YAML
name: ROC curve
|
|
description: Calculates Receiver Operating Characteristic curve. See https://en.wikipedia.org/wiki/Receiver_operating_characteristic
|
|
inputs:
|
|
- {name: Predictions dir, type: GCSPath, description: 'GCS path of prediction file pattern.'} #TODO: Replace dir data + schema files # type: {GCSPath: {path_type: Directory}}
|
|
- {name: True class, type: String, default: 'true', description: 'The true class label for the sample. Default is "true".'}
|
|
- {name: True score column, type: String, default: 'true', description: 'The name of the column for positive probability.'}
|
|
- {name: Target lambda, type: String, default: '', description: 'Text of Python lambda function which returns boolean value indicating whether the classification result is correct.\nFor example, "lambda x: x[''a''] and x[''b'']". If missing, input must have a "target" column.'}
|
|
- {name: Output dir, type: GCSPath, description: 'GCS path of the output directory.'} #TODO: Replace dir with single file # type: {GCSPath: {path_type: Directory}}
|
|
#outputs:
|
|
# - {name: UI metadata, type: UI metadata}
|
|
# - {name: Metrics, type: Metrics}
|
|
implementation:
|
|
container:
|
|
image: gcr.io/ml-pipeline/ml-pipeline-local-confusion-matrix:151c5349f13bea9d626c988563c04c0a86210c21
|
|
command: [python2, /ml/roc.py]
|
|
args: [
|
|
--predictions, {inputValue: Predictions dir},
|
|
--trueclass, {inputValue: True class},
|
|
--true_score_column, {inputValue: True score column},
|
|
--target_lambda, {inputValue: Target lambda},
|
|
--output, {inputValue: Output dir},
|
|
]
|
|
# fileOutputs:
|
|
# UI metadata: /mlpipeline-ui-metadata.json
|
|
# Metrics: /mlpipeline-metrics.json
|