Making a Prediction Using a Model via REST API

Overview

Description	Make a prediction using a model.
Resource Path	`/api/models/predict?percentile={percentileValue}`
HTTP Method	POST
Request/Response Format	application/json

Parameter description

Parameter	Description
`{skipDecoding}`	If this property is set to true, the predicted value is not decoded. This is an optional parameter.
`{percentileValue}`	The percentile value for the prediction. This should be a double value between 0-100. It is required to specify a percentile value when the ML model uses an algorithm of the `Anomaly Detection` type. This property is optional for other algorithm types. For more information about algorithms of the `Anomaly Detection` type, see Machine Learner Algorithms.

If you are using a deep learning model to make predictions without H2O runtime, see Using Deep Learning Models without H2O Runtime.

Sample cURL command

curl -X POST -b cookies  https://localhost:9443/api/models/predict -H "Authorization: Basic YWRtaW46YWRtaW4=" -H "Content-Type: multipart/form-data" -F modelId='1' -F dataFormat='csv' -F file=@'test-file.csv' -k
 
curl -X POST -b cookies  https://localhost:9443/api/models/predict?skipDecoding=true -H "Authorization: Basic YWRtaW46YWRtaW4=" -H "Content-Type: multipart/form-data" -F modelId='1' -F dataFormat='csv' -F file=@'test-file.csv' -k

test-file.csv
2,197,70,45,543,30.5,0.158,53
10,125,70,26,115,31.1,0.205,41
7,159,64,0,0,27.4,0.294,40
5,99,74,27,0,29.0,0.203,32
2,92,62,28,0,31.6,0.130,24
1,126,60,0,0,30.1,0.349,47
1,93,70,31,0,30.4,0.315,23

Example - 1

POST https://localhost:9443/api/models/predict

Sample output

["0","0","0","0","0","0","0"]

Example - 2

POST https://localhost:9443/api/models/predict?skipDecoding=true

Sample output

["0.21","0.11","0.12","0.04","0.09","0.01","0.32"]

REST API response

HTTP status code

200, 404 or 500

For descriptions of the HTTP status codes, see HTTP Status Codes.