Joyful Insights Forecasting AI API

API ID 6822

The Joyful Insights Forecasting (AI) API delivers emotional classification results, categorizing input data as either 'Happy' or 'Unhappy'. Utilizing advanced machine learning techniques, this API specializes in sentiment analysis to provide accurate predictions. For further details about the underlying model and its capabilities, please reach out to us.

100% uptime 228 ms avg response

API Documentation

Endpoints

Request
EXAMPLE USE OF "/hapiness" endpoint for required input parameters:CALL: /hapiness?X1=3&X2=3&X3=5&X4=3&X5=4&X6=4RESPONSE:
{
    "Value Prediction": "Happy"
}
Endpoint ID: 10309
GET https://zylalabs.com/api/6822/joyful+insights+forecasting+ai+api/10309/hapiness
INPUT PARAMETERS

hapiness — Endpoint Features

Object Description
X1 Required the availability of information about the city services
X2 Required the cost of housing
X3 Required the overall quality of public schools
X4 Required your trust in the local police
X5 Required the maintenance of streets and sidewalks
X6 Required the availability of social community events

Free test requests remaining: 3 of 3.


INPUT PARAMETERS

X1
X2
X3
X4
X5
X6
API EXAMPLE RESPONSE
JSON
{
  "Value Prediction": "Happy"
}
Hapiness — CODE SNIPPETS

curl --location --request GET 'https://zylalabs.com/api/6822/joyful+insights+forecasting+ai+api/10309/hapiness?X1=Required&X2=Required&X3=Required&X4=Required&X5=Required&X6=Required' --header 'Authorization: Bearer YOUR_API_KEY' 


    
Request

List all vars and possible values.

Endpoint ID: 10310
GET https://zylalabs.com/api/6822/joyful+insights+forecasting+ai+api/10310/listallvars
INPUT PARAMETERS

Free test requests remaining: 3 of 3.


INPUT PARAMETERS

This endpoint does not require any input parameters.

API EXAMPLE RESPONSE
JSON
{
  "X1": "the availability of information about the city services",
  "X2": "the cost of housing",
  "X3": "the overall quality of public schools",
  "X4": "your trust in the local police",
  "X5": "the maintenance of streets and sidewalks",
  "X6": "the availability of social community events"
}
Listallvars — CODE SNIPPETS

curl --location --request GET 'https://zylalabs.com/api/6822/joyful+insights+forecasting+ai+api/10310/listallvars' --header 'Authorization: Bearer YOUR_API_KEY' 


    
Request

 Info for this API ()

Endpoint ID: 10311
GET https://zylalabs.com/api/6822/joyful+insights+forecasting+ai+api/10311/info
INPUT PARAMETERS

Free test requests remaining: 3 of 3.


INPUT PARAMETERS

This endpoint does not require any input parameters.

API EXAMPLE RESPONSE
JSON
{
  "API Info:": "This API requests per values provide class result ('Happy' or 'Unhappy'). The AI algorithm consists of ML (Machine Learning) techniques for Classification task. Please contact us for more information about the model. We acknowledge the researchers involved in this study and thank them for providing the Dataset for Analysis. We here cite the dataset: 'Koczkodaj, W. (2017). Somerville Happiness Survey [Dataset]. UCI Machine Learning Repository. https://doi.org/10.24432/C5PW36.'"
}
Info — CODE SNIPPETS

curl --location --request GET 'https://zylalabs.com/api/6822/joyful+insights+forecasting+ai+api/10311/info' --header 'Authorization: Bearer YOUR_API_KEY' 


    

API Access Key & Authentication

After signing up, every developer is assigned a personal API access key, a unique combination of letters and digits provided to access to our API endpoint. To authenticate with the Joyful Insights Forecasting AI API simply include your bearer token in the Authorization header.

Headers
Header Description
Authorization Required Should be Bearer access_key. See "Your API Access Key" above when you are subscribed.

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Overview

This API request provides a class result ('Happy' or 'Unhappy') based on a requested mini-survey with answers ranging from 1 (Totally Disagree) to 5 (Totally Agree). The AI algorithm consists of ML (Machine Learning) techniques for the Classification task. For more information about the model, please contact us. We acknowledge the researchers involved in this study and thank them for providing the Dataset for Analysis. We here cite the dataset: 'Koczkodaj, W. (2017). Somerville Happiness Survey [Dataset]. UCI Machine Learning Repository.'

Joyful Insights Forecasting AI API FAQs

The "hapiness" endpoint returns a classification result indicating emotional state as either 'Happy' or 'Unhappy'. The "listallvars" endpoint provides a list of variables related to factors influencing happiness, while the "info" endpoint offers general information about the API and its underlying model.

The "hapiness" endpoint response includes "Value Prediction" indicating the emotional classification. The "listallvars" response contains variable names (e.g., "X1", "X2") and their descriptions, while the "info" endpoint provides a summary of the API's functionality and data sources.

Responses are structured in JSON format. For "hapiness", it returns a single key-value pair. The "listallvars" endpoint returns multiple key-value pairs for each variable, and the "info" endpoint provides a comprehensive overview in a single JSON object.

The "hapiness" endpoint provides emotional classifications, the "listallvars" endpoint details various factors affecting happiness, and the "info" endpoint gives insights into the API's functionality and data sources.

Currently, the API does not support customizable parameters for the "hapiness" or "listallvars" endpoints. Users can simply call these endpoints to receive the predefined data. Future enhancements may allow for more tailored requests.

The data utilized by the Joyful Insights Forecasting AI API is based on the Somerville Happiness Survey dataset, provided by Koczkodaj, W. (2017). This dataset is available in the UCI Machine Learning Repository, ensuring a reliable source for analysis.

Typical use cases include sentiment analysis for social research, understanding community well-being, and enhancing user experience in applications that require emotional insights. The data can help organizations gauge public sentiment on various issues.

Users can leverage the "hapiness" classification to assess emotional trends in their data, while the "listallvars" information can guide them in identifying key factors influencing happiness. This can inform decision-making in community planning or service improvements.

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