BuildRegressionForecastByInterval

POST

https://api.cbf.tcn.com/api/v1alpha1/wfm/buildregressionforecastbyinterval

Generates a regression forecast using the provided @regression_template.
It will generate forecast intervals for the skill profiles sids in @skill_profile_sids_to_forecast.
It will use the client's saved forecasting test range as the start datetime and the forecast range as the end datetime of the forecasted data.
It will use the client's saved interval width to divide the resulting forecast intervals.
Errors:

grpc.Invalid: no @skill_profile_sids_to_forecast are given or the @regression_template in the request is invalid.

grpc.Internal: error occurs during the building of the regression forecast.

Request

Authorization

JWT Bearer

Add the parameter

Authorization

to Headers

Example:

Authorization: ********************

Body Params application/jsonRequired

Example

{
    "average_speed_of_answer_in_seconds": 0,
    "average_handle_time_in_seconds": 0,
    "average_after_call_work_in_seconds": 0,
    "average_time_to_abort_in_seconds": 0,
    "regression_template": {
        "regression_template_sid": 0,
        "name": "string",
        "model_type": "RANDOM_FOREST",
        "exclude_call_data_for_n_weeks": 0,
        "num_weeks_ago_to_emphasize": 0,
        "max_deviation": 0,
        "trend_sensitivity": 0,
        "exclude_intervals_with_no_calls": true,
        "avgs_processing_type": "FORECAST",
        "include_seasonality": true,
        "include_trend": true
    },
    "skill_profile_sids_to_forecast": [
        0
    ],
    "average_talk_time_in_seconds": 0
}

Request Code Samples

Shell

JavaScript

Java

Swift

PHP

Python

HTTP

Objective-C

Ruby

OCaml

Dart

curl --location --request POST 'https://api.cbf.tcn.com/api/v1alpha1/wfm/buildregressionforecastbyinterval' \
--header 'Authorization: Bearer <token>' \
--header 'Content-Type: application/json' \
--data-raw '{
    "average_speed_of_answer_in_seconds": 0,
    "average_handle_time_in_seconds": 0,
    "average_after_call_work_in_seconds": 0,
    "average_time_to_abort_in_seconds": 0,
    "regression_template": {
        "regression_template_sid": 0,
        "name": "string",
        "model_type": "RANDOM_FOREST",
        "exclude_call_data_for_n_weeks": 0,
        "num_weeks_ago_to_emphasize": 0,
        "max_deviation": 0,
        "trend_sensitivity": 0,
        "exclude_intervals_with_no_calls": true,
        "avgs_processing_type": "FORECAST",
        "include_seasonality": true,
        "include_trend": true
    },
    "skill_profile_sids_to_forecast": [
        0
    ],
    "average_talk_time_in_seconds": 0
}'

Responses

🟢200OK

application/json

Success

Body

Example

{
    "start_datetime": "1s",
    "skill_profile_sid": 0,
    "total_calls": 0,
    "average_speed_of_answer_in_seconds": 0,
    "average_handle_time_in_seconds": 0,
    "average_after_call_work_in_seconds": 0,
    "average_time_to_abort_in_seconds": 0,
    "total_abandoned_calls": 0,
    "is_delta": true,
    "forecast_data_interval_sid": 0,
    "interval_width_in_minutes": 0,
    "skill_profile_category": {
        "skill_profile_category_sid": 0,
        "skill_profile_category_type": "SINGLE_SKILL_PROFILE"
    },
    "average_talk_time_in_seconds": 0
}

🟢200Success

Modified at 2025-09-26 15:44:58

ListForecastIntervalsV2

BuildRegressionForecastByIntervalWithStats