-
Notifications
You must be signed in to change notification settings - Fork 24
Discretization of Continuous Valued Attributes
Alexander L. Hayes edited this page Oct 23, 2017
·
1 revision
As RDN Boost model accepts discrete values in its input predicate logic form, a new discretization functionality has been added as follows;
- In the mode file, user has to specify the predicate and its arguments to discretize along with the number of bins desired. The discretization uses equal frequency distribution. An example from background file is mentioned below:
For the following predicate hdl(+Patient,#Time, #hdlValue).
We want to discretize the 2nd and 3rd argument and into 2 and 3 bins respectively. disc: hdl([2,3],[2,3]).
Another example For a predicate a1c(+Patient,+a1cValue).
We want to discretize the 1rst argument and into 4 bins. disc: a1c([2],[4]).
BoostSRL Wiki
Home
BoostSRL Basics
- Getting Started
- File Structure
- Basic Usage Parameters
- Advanced Usage Parameters
- Basic Modes Guide
- Advanced Modes Guide
Deep dive into BoostSRL
- Default (RDN-Boost)
- MLN-Boost
- Regression
- Cost-sensitive SRL
- Learning with Advice
- Approximate Counting
- One-class Classification (coming soon)
- Discretization of Continuous Valued Attributes
- Lifted Relational Random Walks
- Grounded Relational Random Walks
Datasets
Applications of BoostSRL