AutoML
Description
Zia AutoML enables you to train models and analyze a set of training data to predict the outcome of a subset of that data. You can build and train Binary Classification, Multi-Class Classification, and Regression Models, and obtain insightful evaluation reports.
This API is used to pass input for an AutoML model's prediction as key-value pairs. You must pass the data in a JSON format in the request as described below.
- The AutoML model must already be created. You can create and configure a model from the console.
- You can specify the target column, or the column in the dataset whose value needs to be predicted, while configuring the model from the console.
Request URL
https://api.catalyst.zoho.com/baas/v1/project/{project_id}/ml/automl/model/{model_id}
project_id - The unique ID of the project
model_id - The unique ID of the model
Request Headers
Authorization: Zoho-oauthtoken 1000.910***************************16.2f****************************57
Content-Type: application/json
Request Method
POST
Scope
scope=ZohoCatalyst.mlkit.READ
Request JSON Format
You must send the column names and the corresponding column values in a JSON format like this:
{
"column1_name": "column1_value",
"column2_name": "column2_value",
"column3_name": "column3_value"
}
where column_name is a key in the dataset required for predicting the target, and column_value is the data you provide for the corresponding column.
- If you enter a value in a format that does not match the data type of the column, such as a numerical value for the date type, the value will not be parsed. Ensure that you provide the data in the right format.
- You must provide the value for atleast one valid column while testing the prediction.
- If you don't enter the value for an input field, a default value will be entered for the column by Zia automatically. However, this will affect the accuracy of the prediction.
SDK documentation
Sample Request: Regression model
curl -X POST \
https://api.catalyst.zoho.com/baas/v1/project/4000000006007/ml/automl/model/105000000124001 \
-H "Authorization: Zoho-oauthtoken 1000.8cb99dxxxxxxxxxxxxx9be93.9b8xxxxxxxxxxxxxxxf" \
-H "Content-Type: application/json" \
-d '{
"country": "Armenia",
"year": "2016",
"sex": "female",
"age": "25-34",
"population": "277452",
"GDP_for_year": "10,546,135,160"
}'
Sample Response: Regression model
{
"status":"success",
"data":{
"regression_result":3.41
}
}
Sample Request: Binary-class classification model
curl -X POST \
https://api.catalyst.zoho.com/baas/v1/project/4000000006007/ml/automl/model/105000000124001 \
-H "Authorization: Zoho-oauthtoken 1000.8cb99dxxxxxxxxxxxxx9be93.9b8xxxxxxxxxxxxxxxf" \
-H "Content-Type: application/json" \
-d '{
"year_film": "2019",
"year_award": "2020",
"ceremony": "77",
"category": "Best Director - Motion Picture",
"nominee": "Todd Phillips",
"film": "Joker"
}'
Sample Response: Binary-class classification model
{
"status":"success",
"data":{
"classification_result":
{
"True":20,
"False":80
}
}
}
Sample Request: Multi-class classification model
curl -X POST \
https://api.catalyst.zoho.com/baas/v1/project/4000000006007/ml/automl/model/105000000124001 \
-H "Authorization: Zoho-oauthtoken 1000.8cb99dxxxxxxxxxxxxx9be93.9b8xxxxxxxxxxxxxxxf" \
-H "Content-Type: application/json" \
-d '{
"Transaction_date": "1/2/09 4:53",
"Product": "RAM",
"Price": "120",
"City": "Parkville",
"State": "MO",
"Country": "United States",
"Account_Created": "12/4/08 4:42",
"Last_Login": "1/2/09 7:49"
}'
Sample Response: Multi-class classification model
{
"status":"success",
"data":{
"classification_result":
{
"Amex":10,
"Diner":20,
"Mastercard": 30,
"Visa":40
}
}
}