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On this page
  • Sample Request
  • Building an Auto Structured Data Regressor
  • Automated Model Construction
  • Sample Request
  • Training an Auto Structured Data Regressor
  • Automated Model Training
  • Predictions

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  1. Autogon Engine (Studio)
  2. Automated Deep Learning

Auto Structured Data Regression (A_DL_SDR)

This function creates an Automated Structured Data regression model

This is a type of machine learning model that is designed to predict a continuous numerical output based on a set of input features that are structured in a tabular format.

Sample Request

Build an Auto Structured Data Regressor

{
    "project_id": 1,
    "parent_id": 7,
    "block_id": 8,
    "function_code": "A_DL_SDR_I",
    "args": {
    "hyp_params":{
            "max_trials": 1
        }
    }
}

Building an Auto Structured Data Regressor

Automated Model Construction

POST https://autogon.ai/api/v1/engine/start

Request Body

Name
Type
Description

project_id*

int

The id of the current project

block_id*

int

The id of the current block

function_code*

string

The function code for current block

parent_id*

int

The id of the previous block

args*

object

Block arguments

max_trials

int

Maximum number of different models that will be tried

{
    "status": "true",
    "message": {
        "id": 8,
        "project": 1,
        "block_id": 8,
        "parent_id": 7,
        "dataset_url": "",
        "x_value_url": "",
        "y_value_url": "",
        "x_train_url": "",
        "y_train_url": "",
        "x_test_url": "",
        "y_test_url": "",
        "output": {}
    }
}

Sample Request

Compile and train the pre-built SDR model, using passed in Hyper Parameters

{
    "project_id": 1,
    "parent_id": 8,
    "block_id": 9,
    "function_code": "A_DL_SDR_T",
    "args": {
        "model_name": "titanic_model",
        "hyp_params":{
            "epochs": 10
        }
    }
}

Training an Auto Structured Data Regressor

Automated Model Training

POST https://autogon.ai/api/v1

Request Body

Name
Type
Description

project_id*

int

The id of the current project

hyp_params

object

hyper parameters for model compilation and training

parent_id*

int

The id of the previous block

block_id*

int

The id of the current block

function_code*

The function code for current block

args*

object

Block arguments

model_name*

String

The name the model would be saved with

epochs

int

Number of iterations through the dataset

{
    "status": "true",
    "message": {
        "id": 9,
        "project": 1,
        "block_id": 9,
        "parent_id": 8,
        "dataset_url": "",
        "x_value_url": "",
        "y_value_url": "",
        "x_train_url": "",
        "y_train_url": "",
        "x_test_url": "",
        "y_test_url": "",
        "output": {}
    }
}

Predictions

Make predictions with the DL_ANN Predict block

// Some code
// Some code
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Last updated 1 year ago

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