Objective-C / Cognite API v1 / Create entity matcher model
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#import <CkoHttp.h>
#import <CkoJsonObject.h>
#import <CkoHttpResponse.h>
// This example assumes the Chilkat API to have been previously unlocked.
// See Global Unlock Sample for sample code.
CkoHttp *http = [[CkoHttp alloc] init];
BOOL success;
// Use this online tool to generate code from sample JSON: Generate Code to Create JSON
// The following JSON is sent in the request body.
// {
// "sources": [
// {},
// {}
// ],
// "targets": [
// {},
// {}
// ],
// "trueMatches": [
// [
// ],
// [
// ]
// ],
// "externalId": "in irure amet",
// "name": "minim",
// "description": "aliqua ipsum culpa eiusmod",
// "featureType": "simple",
// "matchFields": [
// {
// "source": "name",
// "target": "name"
// }
// ],
// "classifier": "randomforest",
// "ignoreMissingFields": false
// }
CkoJsonObject *json = [[CkoJsonObject alloc] init];
[json UpdateNewArray: @"trueMatches[0]."];
[json UpdateNewArray: @"trueMatches[1]."];
[json UpdateString: @"externalId" value: @"in irure amet"];
[json UpdateString: @"name" value: @"minim"];
[json UpdateString: @"description" value: @"aliqua ipsum culpa eiusmod"];
[json UpdateString: @"featureType" value: @"simple"];
[json UpdateString: @"matchFields[0].source" value: @"name"];
[json UpdateString: @"matchFields[0].target" value: @"name"];
[json UpdateString: @"classifier" value: @"randomforest"];
[json UpdateBool: @"ignoreMissingFields" value: NO];
[http SetRequestHeader: @"content-type" value: @"application/json"];
[http SetRequestHeader: @"api-key" value: @"{{api-key}}"];
CkoHttpResponse *resp = [http PostJson3: @"https://domain.com/api/v1/projects/{{project}}/context/entitymatching" contentType: @"application/json" json: json];
if (http.LastMethodSuccess == NO) {
NSLog(@"%@",http.LastErrorText);
return;
}
NSLog(@"%d",[resp.StatusCode intValue]);
NSLog(@"%@",resp.BodyStr);
Curl Command
curl -X POST
-H "api-key: {{api-key}}"
-H "content-type: application/json"
-d '{
"sources": [
{},
{}
],
"targets": [
{},
{}
],
"trueMatches": [
[],
[]
],
"externalId": "in irure amet",
"name": "minim",
"description": "aliqua ipsum culpa eiusmod",
"featureType": "simple",
"matchFields": [
{
"source": "name",
"target": "name"
}
],
"classifier": "randomforest",
"ignoreMissingFields": false
}'
https://domain.com/api/v1/projects/{{project}}/context/entitymatching
Postman Collection Item JSON
{
"id": "entityMatchingCreate",
"name": "Create entity matcher model",
"request": {
"url": {
"host": "{{baseUrl}}",
"path": [
"api",
"v1",
"projects",
"{{project}}",
"context",
"entitymatching"
],
"query": [
],
"variable": [
]
},
"method": "POST",
"header": [
{
"key": "api-key",
"value": "{{api-key}}",
"description": "An admin can create API keys in the Cognite console."
},
{
"key": "content-type",
"value": "application/json"
}
],
"description": "Note: All users on this CDF subscription with assets read-all and entitymatching read-all and write-all capabilities in the project, are able to access the data sent to this endpoint. Train a model that predicts matches between entities (for example, time series names to asset names). This is also known as fuzzy joining. If there are no trueMatches (labeled data), you train a static (unsupervised) model, otherwise a machine learned (supervised) model is trained.",
"body": {
"mode": "raw",
"raw": "{\n \"sources\": [\n {},\n {}\n ],\n \"targets\": [\n {},\n {}\n ],\n \"trueMatches\": [\n [],\n []\n ],\n \"externalId\": \"in irure amet\",\n \"name\": \"minim\",\n \"description\": \"aliqua ipsum culpa eiusmod\",\n \"featureType\": \"simple\",\n \"matchFields\": [\n {\n \"source\": \"name\",\n \"target\": \"name\"\n }\n ],\n \"classifier\": \"randomforest\",\n \"ignoreMissingFields\": false\n}"
}
}
}