joschout/LazyBum
Source code related to the ILP 2019 paper 'LazyBum: Decision tree learning using lazy propositionalization'
This project helps data analysts and researchers extract meaningful patterns from complex relational databases by summarizing them into a single table, then building a decision tree to classify entries. You provide a database with a target table for classification, and it outputs a feature table and a decision tree model. This is for professionals who work with interconnected data and need to build classification models.
No commits in the last 6 months.
Use this if you need to build a decision tree classifier on a relational database and want an efficient way to automatically generate relevant features from across your connected tables.
Not ideal if your data is not in a relational database or you need to predict numerical outcomes instead of categories.
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Language
Java
License
Apache-2.0
Category
Last pushed
Jan 22, 2021
Commits (30d)
0
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