SymetryML Documentation
Learning

Forget frame data

Forgets a raw `DataFrame` posted inline — the inverse of `learn`. Set `async=true` to run as a background job (`202`, job id in the `sym-job-id` header, empty body); without it, forgetting happens synchronously and the `200` response body has empty `values`. Not supported on `sequence`-type projects.

POST
/{user}/projects/{project}/forget

Forgets a raw DataFrame posted inline — the inverse of learn. Set async=true to run as a background job (202, job id in the sym-job-id header, empty body); without it, forgetting happens synchronously and the 200 response body has empty values. Not supported on sequence-type projects.

Authorization

SymetryMLAuth
AuthorizationBearer <token>

HMAC-SHA256 signature-based authentication: requests are signed with your secret key and sent with the Customer-ID, Sym-date, Authorization, Content-MD5 and sym-version headers. See SymetryML REST API Security for the signature algorithm and a complete example.

In: header

Path Parameters

user*string

User/Customer identifier

project*string

Project identifier

Query Parameters

async?boolean

Request Body

application/json

TypeScript Definitions

Use the request body type in TypeScript.

Response Body

application/json

application/json

application/json

application/json

curl -X POST "https://example.com/c1/projects/nbra_prj_iris/forget" \  -H "Content-Type: application/json" \  -d '{    "attributeNames": [      "sepal_length",      "sepal_width",      "petal_length",      "petal_width",      "Iris_setosa"    ],    "attributeTypes": [      "C",      "C",      "C",      "C",      "B"    ],    "data": [      [        "5.1",        "3.5",        "1.4",        "0.2",        "1"      ]    ]  }'
{  "statusCode": 200,  "statusString": "OK",  "values": {}}
{  "statusCode": 202,  "statusString": "Job Created",  "values": {}}

{  "statusCode": 400,  "statusString": "Cannot forget sequence project, id[seq_prj], cid [c1]",  "values": {}}

{  "statusCode": 500,  "statusString": "Generic Throwable [com.google.gson.JsonSyntaxException: com.google.gson.stream.MalformedJsonException: Unterminated object at line 1 column 21 path $.evil_hack]",  "values": {}}

Learn from a registered data source POST

Learns from a registered data source (as opposed to `learn`, which learns from a small `DataFrame` posted inline). Unlike `learn`, there is no `async` query parameter — this endpoint is **always** asynchronous: it immediately returns `202` with the job id in the `sym-job-id` response header and an empty body. Poll `GET /{user}/jobs/{jobId}` with that id for completion/progress; this endpoint's own response is never a job-status payload. The `DataFrame` request body carries no data rows — it only specifies the `attributeNames`/`attributeTypes` to use when learning from the data source's own data.

Learn frame data POST

Learns from a raw `DataFrame` posted inline (as opposed to `dss/{dsName}/learn`, which learns from a registered data source via an always-async job). Set `async=true` to run as a background job — the response is `202` with the job id in the `sym-job-id` header and an empty body; poll `GET /{user}/jobs/{jobId}` for completion. Without `async` (or `async=false`), learning happens synchronously and the `200` response body has empty `values` — it is not a job-status payload.