SKL Runner

The SKL runner is responsible for executing a trained ML models (Regression & classification) to make predictions or perform tasks. It takes input data, applies the model's knowledge, and generates the desired output.

Method: POST Authorization: API Key

https://engine.raccoon-ai.io/api/v1/runner/skl/<permanent_model_id>

Important: To use SKL runner, first you need to make train model with trainer and make that cached model to permanent model.

Authorization

Type	Key	Value
API Key	X-Api-Key	rae_##########

Request Body

Section	Key	Data Type	Required	Description
train	data	json	true	Data that use to train the model
	features	list	true	Input features (X)
	targets	list	true	Output targets (y)
	config	json	false	Train configurations
project	project_id	string	true	ID of the project

Types

{
    "data":<json>,
    "config": <json>
}

Sample

{
  "data": {
    "R&D Spend": {
      "0": 165349.2,
      "1": 162597.7,
      "2": 153441.51,
      "3": 144372.41,
      "4": 142107.34
    },
    "Administration": {
      "0": 136897.8,
      "1": 151377.59,
      "2": 101145.55,
      "3": 118671.85,
      "4": 91391.77
    },
    "Marketing Spend": {
      "0": 471784.1,
      "1": 443898.53,
      "2": 407934.54,
      "3": 383199.62,
      "4": 366168.42
    },
    "State": {
      "0": "New York",
      "1": "California",
      "2": "Florida",
      "3": "New York",
      "4": "Florida"
    }
  },
  "config": {
    "include_inputs": true
  }
}

Reponse Body

Key	Data Type	Description
success	boolean	Indicate the success of the request
msg	string	Message indicators
error_code	int	Error code information, only set if success is false
result	json	Result, only set if success is true
gen_at	datetime	Generated datetime

Types

{
    "success": <bool>,
    "msg": <string>,
    "error": <null> or <string>,
    "result": <json>,
    "score": <json>,
    "generated_ts": <timestamp>
}

Sample

{
  "success": true,
  "msg": "Runner predicted successfully",
  "error": null,
  "result": {
    "R&D Spend": {
      "0": 165349.2,
      "1": 162597.7,
      "2": 153441.51,
      "3": 144372.41,
      "4": 142107.34
    },
    "Administration": {
      "0": 136897.8,
      "1": 151377.59,
      "2": 101145.55,
      "3": 118671.85,
      "4": 91391.77
    },
    "Marketing Spend": {
      "0": 471784.1,
      "1": 443898.53,
      "2": 407934.54,
      "3": 383199.62,
      "4": 366168.42
    },
    "State": {
      "0": "New York",
      "1": "California",
      "2": "Florida",
      "3": "New York",
      "4": "Florida"
    },
    "Profit": {
      "0": 190209.72,
      "1": 186863.18,
      "2": 179790.26,
      "3": 171576.92,
      "4": 169898.04
    }
  },
  "score": {
    "train": 0.942446542689397,
    "test": 0.9649618042060305
  },
  "generated_ts": 1686130100.870728
}