Predicting Financial Audit Outcome
This MLHub package contains a decision tree model from the Rattle package for R. It is used in the Rattle book to demonstrate a classification model use-case in financial audit. A sample dataset of audit outcomes is used to train the model to predict the outcome of audits. A successful audit identifies missing or incorrectly reported financial data.
A classification (decision) tree model to represent the discovered knowledge is built using a recursive partitioning algorithm. Decision trees are recognised as an easily understandable representation of the discovered knowledge. They are widely popular in situations where insight and explanations are important.
Visit the github repository for more details: https://github.com/gjwgit/audit
To install and run the pre-built model:
$ pip install mlhub $ ml install audit $ ml configure audit $ ml demo audit $ ml print audit $ ml display audit