---
title: "Regression"
slug: "regression"
updated: 2023-04-24T12:53:39Z
published: 2023-04-24T12:53:39Z
canonical: "docs.interprose.com/regression"
---

> ## Documentation Index
> Fetch the complete documentation index at: https://docs.interprose.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Regression

Linear prediction is a mathematical operation in which the future values of a dependent variable are estimated as a function of previous samples. **The Forecast.Regression** element implements:

- **Simple linear regression**, where values are based on a trend line
- **Autoregression**, which predicts an output based on previous outputs, using the "Burg" method
- **Non-linear regression**, which displays the relationship between dependent and independent variables using a curvilinear function and may provide more accuracy. Available curvilinear functions include:
  - Exponential
  - Logarithmic
  - Polynomial2
  - Polynomial3
  - Polynomial4
  - Polynomial5
  - Power

### Input Data Requirements

Data should conform to the following requirements:

- Dependent data column data should be Numeric data type
- Dependent data column data should not contain NULL values
- Independent data column may have any data type (if data type is not Numeric, independent data column will be replaced with an integer enumeration (1,2,3,...RowCount).
- Dataset should be in ascending order by independent data column value
- Forecast Length attribute should be less than original row count (if user defines Forecast Length as more than row count, Forecast Length value will automatically be truncated to 20% of RowCount)
- Some of the regression methods require a minimum number of rows (for example, Autoregression requires at least one more row than the value of the AutoRegressive Order attribute, and Polynomial3 requires at least four rows)

### Results

As a result of the forecast operation, two new columns will be added to the datalayer. The names of these two columns will be drawn from the element's attributes:

- Forecast Indicator Column ID: this column will contain a boolean flag, set to True if the row contains a forecast value
- Forecast Value Column ID: this column will contain the forecast value for each row of the original dataset

The following table shows the effect on the datalayer of a forecast operation:

![](https://cdn.document360.io/6c7303ca-5ffc-4149-8868-8ea498eee635/Images/Documentation/RB_59.png?sv=2026-02-06&spr=https&st=2026-10-31T22%3A26%3A28Z&se=2026-10-31T23%3A26%3A28Z&sr=c&sp=r&sig=37sR6aKKoOCP7qrQ38GN2eN0rYpvHm5m4LG%2FJ4Qjtuw%3D)