Perform poisson regression with Python.

Purpose

This App provides a tool for fitting data with Poisson Regression model. It fits a dataset with one dependent variable and multiple independent variables. You can further use it to predict the response of independent variables. 

Notes:

• It needs Embedded Python and scikit-learn library. Other dependent libraries include numpy. 

Installation

1. Download the Poisson Regression.opx file, then drag-and-drop onto the Origin workspace.
2. The App will start downloading dependent Python libraries. Wait a few minutes until the download is completed and restart Origin.

Operation

1. Activate a worksheet. Click the App icon to bring up the dialog.
2. On Input Data tab, select single or multiple worksheet columns for Independent Variables and specify Dependent Variable by selecting a single worksheet column.
3. On Options tab, change settings to fit the model
   • Maximum Iterations: Maximum number of iterations. The solver iterates until convergence or this number of iterations.
   • Tolerance: Stop the algorithm if the fitting parameter has converged.
   • Alpha: Constant that multiplies the L2 penalty term and determines the regularization strength.
   • Solver: Algorithm to use in the optimization problem.
   • Include Intercept: Whether to calculate the intercept for this model.  
4. On Prediction tab, you can select a range of independent data to predict the response with the fitted neural network.
5. Click OK to output reports.

v 1.01 sklearn package deprecated fixed.