Commands model:k_means/new¶
Create a ‘new’ instance of a k-means model.
POST /v1/commands/¶
GET /v1/commands/:id¶
Request¶
Route
POST /v1/commands/
Body
| name: | model:k_means/new |
|---|---|
| arguments: | dummy_model_ref : Model
name : unicode (default=None)
|
Headers
Authorization: test_api_key_1
Content-type: application/json
Description
k-means [1] is an unsupervised algorithm used to partition the data into ‘k’ clusters. Each observation can belong to only one cluster, the cluster with the nearest mean. The k-means model is initialized, trained on columns of a frame, and used to predict cluster assignments for a frame. This model runs the MLLib implementation of k-means [2] with enhanced features, computing the number of elements in each cluster during training. During predict, it computes the distance of each observation from its cluster center and also from every other cluster center.
footnotes
| [1] | https://en.wikipedia.org/wiki/K-means_clustering |
| [2] | https://spark.apache.org/docs/1.5.0/mllib-clustering.html#k-means |
Response¶
Status
200 OK
Body
Returns information about the command. See the Response Body for Get Command here below. It is the same.