Regression modeling
This tool allows you to create regression models using the Spotfire Enterprise Runtime for R engine, without the need of writing any scripts yourself.
Note: Regression modeling must be authored in the installed client.
On the menu bar, select to use the tool.
See the various sections for more details.
- Creating a regression model
Use the Regression modeling tool to create regression models using the Spotfire Enterprise Runtime for R engine, without the need of writing any scripts yourself. - Linear regression method
Linear regression models the numeric response column as a weighted sum of the predictor columns. The weights, also known as the regression coefficients, are selected by the method of least squares, which minimizes the sum of the squared differences between the observed response and the predictions based on the weighted sum. - Regression tree method
Regression tree is a nonparametric regression method that creates a binary tree by recursively splitting the data on the predictor values.
- Creating a regression model
Use the Regression modeling tool to create regression models using the Spotfire Enterprise Runtime for R engine, without the need of writing any scripts yourself. - Linear regression method
Linear regression models the numeric response column as a weighted sum of the predictor columns. The weights, also known as the regression coefficients, are selected by the method of least squares, which minimizes the sum of the squared differences between the observed response and the predictions based on the weighted sum. - Regression tree method
Regression tree is a nonparametric regression method that creates a binary tree by recursively splitting the data on the predictor values.
Parent topic: Predictive modeling