UpsertRegressionForecast

Builds a regression forecast for the org using the given @regression_template and saves the resulting intervals in the db.
It will generate forecast intervals for the skill profiles sids in @save_forecasts_for_skill_profile_sids,
if the list is empty or has no valid skill profile sids, it will generate and save forecasts for all active skill profiles.
If any intervals produced already exist in the db, they will be replaced with the ones produced.
Errors:

grpc.Invalid: the @regression_template in the request is invalid.

grpc.Internal: error occurs when upserting the regression forecast.

Request

Authorization

Provide your bearer token in the

Authorization

header when making requests to protected resources.

Example:

Authorization: Bearer ********************

Body Params application/json

Request message for the UpsertRegressionForecast RPC

regression_template

object (RegressionTemplate)

regression_template

optional

Forecast template used to build the regression forecast

model_type

enum<string>

model_type

optional

Selected algorithmic method to be used

Allowed values:

RANDOM_FORESTADABOOSTGRADIENT_BOOSTINGLINEAR_REGRESSIONLINEAR_AVGSEGMENTED_LINEARMLPAUTO

avgs_processing_type

enum<string>

avgs_processing_type

optional

Processing type for the averages.

Allowed values:

FORECASTAVERAGESFIXED_AVERAGES

name

string

name

optional

Name of the regression template.

exclude_call_data_for_n_weeks

integer <int32>

exclude_call_data_for_n_weeks

optional

Number of weeks of training data to exclude when building a forecast.

num_weeks_ago_to_emphasize

integer <int32>

num_weeks_ago_to_emphasize

optional

Number of weeks in the past to emphasize;

max_deviation

number <float>

max_deviation

optional

Value that especificies the max value of deviations to use. Greater deviations than the specified values will be excluded.
optional

trend_sensitivity

number <float>

trend_sensitivity

optional

Percentage from 0 to 100 that specifies the trend sensitivity.

exclude_intervals_with_no_calls

boolean

exclude_intervals_with_no_calls

optional

Whether or not to exclude intervals with no calls.

include_seasonality

boolean

include_seasonality

optional

Whether or not to include seasonality.

include_trend

boolean

include_trend

optional

Whether or not to include trend.

regression_template_sid

integer <int64> | string

regression_template_sid

optional

ID of the regression template.

average_speed_of_answer_in_seconds

number <float>

average_speed_of_answer_in_seconds

optional

the following only apply for avgs_processing_type=RegressionForecasterAvgsProcessingType.FIXED_AVERAGES
optional

average_handle_time_in_seconds

number <float>

average_handle_time_in_seconds

deprecated

Deprecated as of Apr/25/2025: use average_talk_time_in_seconds instead.

average_after_call_work_in_seconds

number <float>

average_after_call_work_in_seconds

optional

average_time_to_abort_in_seconds

number <float>

average_time_to_abort_in_seconds

optional

average_talk_time_in_seconds

number <float>

average_talk_time_in_seconds

optional

optional - average talk duration.

skill_profile_sids_to_forecast

array[integer <int64> | string]

skill_profile_sids_to_forecast

optional

IDs of the skill Profiles of which to save the generated forecast.

Example

{
  "regression_template": {
    "model_type": "RANDOM_FOREST",
    "avgs_processing_type": "FORECAST",
    "name": "string",
    "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,
    "include_seasonality": true,
    "include_trend": true,
    "regression_template_sid": 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,
  "average_talk_time_in_seconds": 0,
  "skill_profile_sids_to_forecast": [
    0
  ]
}

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