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by Ciphix

0

Activity

3.1k

Summary

Summary

This machine learning related activity is used to estimate a model for a binary variable and uses that model to make a one point ahead forecast for the binary variable.

Overview

Overview

The estimated logit model describes a non-linear regression of which the goal is to perform a forecast where the variable we want to predict is either 0 or 1 (binary). The model uses a logistic probability function to determine the relationship between the dependent and the independent variables. The difference in accuracy between this logit model and a linear probability model is shown in the graphs below.

Features

Features

This activity enables processes to make predictions for discrete variables, thus incorporating machine learning in the process. The activity can be used to alleviate certain human decisions within a process which can benefit a multitude of automation projects.

Additional Information

Additional Information

Dependencies

Accord Framework

Code Language

Visual Basic

Runtime

Windows Legacy (.Net Framework 4.6.1)

License & Privacy

Apache

Privacy Terms

Technical

Version

2.0.2aUpdated

May 11, 2020Works with

Studio: 21.10 - 22.10

Certification

Silver Certified

Support

UiPath Community Support

Resources