Automated Data Processing (DP_ADP)

This function automatically cleans and encodes supported data.

Automated data cleaning and pre-processing streamline the preparation of data for machine learning training. These techniques involve identifying and addressing missing values, outliers, and inconsistencies in the dataset, as well as standardizing and transforming features. By automating these tasks, data scientists can save time, ensure data quality, and enhance the performance and reliability of machine learning models.

Sample Request

{
    "project_id": 1,
    "parent_id": 0,
    "block_id": 1,
    "function_code": "DP_ADP",
    "args": {
        "clean": true,
        "dataset_type": "any",
        "le_thresh": 2
        "load_name": "generated",
        "ohe_thresh": 10,
        "save_name": "generated",
        "strategy_value": "mean",
        "test_size_value": 0.25,
        "x_slice": ":-1",
        "y_slice": "-1"
    }
}

Automated Data Preprocessing

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

Request Body

Name	Type	Description
x_slice*	String | array	boundaries for the x dataset
y_slice*	String | array	boundaries for the y dataset
strategy_value	String	method of handling missing values. Check the Missing Data block
le_thresh	int	uniques threshold for label encoding
ohe_thresh	int	uniques threshold for one hot encoding
project_id*	int	current project ID
block_id*	int	current block ID
function_code*	String	block's function code
args*	object	block arguments
parent_id	int	previous block ID
excluded_columns*	array	Columns to ignore entirely
excluded_fillmissing_columns	array	Columns to ignore for filling in missing data only
excluded_encoding_columns	array	Columns to ignore for encoding only
excluded_scaling_columns	array	Columns to ignore for scaling only
save_name*	String	name to save processing models with
load_name*	String	name to load processing models with. Used to switch to loading mode
dataset_type	String	type of dataset being processed with loaded weights. load_name required
clean	bool	set's wether or not to drop duplicates during loading mode load_name required

200: OK Data Input Successful

{
    "status": "true",
    "message": {
        "id": 1,
        "project": 2,
        "block_id": 1,
        "parent_id": 0,
        "dataset_url": "",
        "x_value_url": "",
        "y_value_url": ""
    }
}

Python

// Some code

Node

Good to know: Unlike other block requests, the Data Input block isn't permitted to have parent blocks, hence its null value.