Auto Text Regression (A_DL_TXR)

This function creates an Automated Text regression model

This model is used for predicting a continuous numeric value given some text input. This model is particularly useful for solving problems such as sentiment analysis, where the goal is to predict the sentiment of a text as a real number between -1 and 1, or price prediction, where the goal is to predict the price of a product based on its description.

Sample Request

Build an Auto Text Regressor

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

Building an Auto Text 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

200 Statemanagement object

{
    "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 TXR model, using passed in Hyper Parameters

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

Training an Auto Text 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

200: OK Statemanagement Object

{
    "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

Python

// Some code

Node