AbductiveLearning
/
ABLkit
Not watched
1
0
Fork 0
Code
Releases 0 Wiki evaluate Activity
Issues 0 Pull Requests 0 Datasets Model Cloudbrain HPC
You can not select more than 25 topics Topics must start with a chinese character,a letter or number, can include dashes ('-') and can be up to 35 characters long.
579 Commits
4 Branches
27 MB
0 Download
 
 
Tree: 322d514997
Branches Tags
${ item.name }
Create branch ${ searchTerm }
from '322d514997'
${ noResults }
ABLkit/examples/zoo
Gao Enhao 322d514997 [MNT] sort import of python files 1 year ago
..
README.md [ENH] add zoo example, resolve comments 1 year ago
get_dataset.py [MNT] sort import of python files 1 year ago
kb.py [MNT] sort import of python files 1 year ago
main.py [MNT] sort import of python files 1 year ago
requirements.txt [ENH] add hed example 1 year ago
zoo.ipynb [DOC, MNT] remove remove import from examples (con't) 1 year ago

README.md

Zoo Example

This example shows a simple implementation of Zoo. In this task, attributes of animals (such as presence of hair, eggs, etc.) and their targets (the animal class they belong to) are given, along with a knowledge base which contain information about the relations between attributes and targets, e.g., Implies(milk == 1, mammal == 1). The goal of this task is to develop a learning model that can predict the targets of animals based on their attributes.

Run

pip install -r requirements.txt
python main.py

Usage

usage: main.py [-h] [--loops LOOPS] 

Zoo example

optional arguments:
  -h, --help            show this help message and exit
  --loops LOOPS         number of loop iterations (default : 3)
Delete task

Are you sure you want to delete this task? Once this task is deleted, it cannot be recovered.

cancel
confirm

An efficient Python toolkit for Abductive Learning (ABL), a novel paradigm that integrates machine learning and logical reasoning in a unified framework.

Python other