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File Structure
by: Tushar Khot, Alexander L. Hayes
Previous Page: "Getting Started" | BoostSRL Wiki | Next Page: "Basic Usage Parameters"
Files that BoostSRL operates on are stored in a folder with three things:
-
background.txt
: Modes -
train/
folder :
-
train_bk.txt
: Pointer to the background file. -
train_facts.txt
: Facts -
train_pos.txt
: Positive examples -
train_neg.txt
: Negative examples
-
test/
folder :
-
test_bk.txt
: Pointer to the background file. -
test_facts.txt
: Facts -
test_pos.txt
: Positive examples -
test_neg.txt
: Negative examples
Example:
File structure for the Cora dataset, notice that the background is called "cora_bk.txt" in this example.
This is okay if train_bk.txt
and test_bk.txt
both point correctly with: import: "../cora_bk.txt".
Table of Contents | BoostSRL Wiki
After training/testing, more files and folders will appear. This advanced guide explains what each of them are, including the contents of the models
, dotFiles
, bRDNs
, and WILLtheories
directories.
Table of Contents | BoostSRL Wiki
Previous Page: "Getting Started" | BoostSRL Wiki | Next Page: "Basic Usage Parameters"
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