Additional domain-specific parameters, any string must be up to 25000
characters long.
For Image Classification:
score_threshold - (float) A value from 0.0 to 1.0. When the model
makes predictions for an image, it will only produce results that have
at least this confidence score. The default is 0.5.
For Image Object Detection:
score_threshold - (float) When Model detects objects on the image,
it will only produce bounding boxes which have at least this
confidence score. Value in 0 to 1 range, default is 0.5.
max_bounding_box_count - (int64) No more than this number of bounding
boxes will be returned in the response. Default is 100, the
requested value may be limited by server.
For Tables:
feature_imp<span>ortan</span>ce - (boolean) Whether feature importance
should be populated in the returned TablesAnnotation.
The default is false.
Additional domain-specific parameters, any string must be up to 25000
characters long.
For Image Classification:
score_threshold - (float) A value from 0.0 to 1.0. When the model
makes predictions for an image, it will only produce results that have
at least this confidence score. The default is 0.5.
For Image Object Detection:
score_threshold - (float) When Model detects objects on the image,
it will only produce bounding boxes which have at least this
confidence score. Value in 0 to 1 range, default is 0.5.
max_bounding_box_count - (int64) No more than this number of bounding
boxes will be returned in the response. Default is 100, the
requested value may be limited by server.
For Tables:
feature_imp<span>ortan</span>ce - (boolean) Whether feature importance
should be populated in the returned TablesAnnotation.
The default is false.
Additional domain-specific parameters, any string must be up to 25000
characters long.
For Image Classification:
score_threshold - (float) A value from 0.0 to 1.0. When the model
makes predictions for an image, it will only produce results that have
at least this confidence score. The default is 0.5.
For Image Object Detection:
score_threshold - (float) When Model detects objects on the image,
it will only produce bounding boxes which have at least this
confidence score. Value in 0 to 1 range, default is 0.5.
max_bounding_box_count - (int64) No more than this number of bounding
boxes will be returned in the response. Default is 100, the
requested value may be limited by server.
For Tables:
feature_imp<span>ortan</span>ce - (boolean) Whether feature importance
should be populated in the returned TablesAnnotation.
The default is false.
Additional domain-specific parameters, any string must be up to 25000
characters long.
For Image Classification:
score_threshold - (float) A value from 0.0 to 1.0. When the model
makes predictions for an image, it will only produce results that have
at least this confidence score. The default is 0.5.
For Image Object Detection:
score_threshold - (float) When Model detects objects on the image,
it will only produce bounding boxes which have at least this
confidence score. Value in 0 to 1 range, default is 0.5.
max_bounding_box_count - (int64) No more than this number of bounding
boxes will be returned in the response. Default is 100, the
requested value may be limited by server.
For Tables:
feature_imp<span>ortan</span>ce - (boolean) Whether feature importance
should be populated in the returned TablesAnnotation.
The default is false.
Additional domain-specific parameters, any string must be up to 25000
characters long.
For Image Classification:
score_threshold - (float) A value from 0.0 to 1.0. When the model
makes predictions for an image, it will only produce results that have
at least this confidence score. The default is 0.5.
For Image Object Detection:
score_threshold - (float) When Model detects objects on the image,
it will only produce bounding boxes which have at least this
confidence score. Value in 0 to 1 range, default is 0.5.
max_bounding_box_count - (int64) No more than this number of bounding
boxes will be returned in the response. Default is 100, the
requested value may be limited by server.
For Tables:
feature_imp<span>ortan</span>ce - (boolean) Whether feature importance
should be populated in the returned TablesAnnotation.
The default is false.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Hard to understand","hardToUnderstand","thumb-down"],["Incorrect information or sample code","incorrectInformationOrSampleCode","thumb-down"],["Missing the information/samples I need","missingTheInformationSamplesINeed","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2025-01-27 UTC."],[],[]]