A prototype Python package for inferring datatypes and converting them into a relational schema. Written in pure Python.
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Prerequisites
- Python (2.7, 3.3, 3.4, 3.5, 3.6)
collections,argparse,re: these should usually be installed already.
Installation
git clone https://github.com/batflyer/Mode-Inference.git
Quick-Start Guide
After you clone the repository:
cd Mode-Inference
# Create a directory for your datasets.
mkdir datasets
# Download one of the datasets from GitHub
curl -L https://github.com/boost-starai/BoostSRL-Misc/blob/master/Datasets/Toy-Cancer/Toy-Cancer.zip?raw=true > datasets/Toy-Cancer.zip
curl -L https://github.com/boost-starai/BoostSRL-Misc/blob/master/Datasets/Toy-Father/Toy-Father.zip?raw=true > datasets/Toy-Father.zip
# Unzip the Data
cd datasets
unzip Toy-Father.zip
# Infer modes:
python inferModes.py -pos datasets/Father/train/train_pos.txt -neg datasets/Father/train/train_neg.txt -fac datasets/Father/train/train_facts.txt
This software is in the early alpha stage: some features may simply not work, others may work but produce unexpected results. Nevertheless: suggestions, issues, general feedback, and pull requests are all welcome.
We use SemVer for versioning. See Releases for all stable versions that are available.
BSD 2-Clause License
Copyright (c) 2018, Alexander L. Hayes
All rights reserved.
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:
* Redistributions of source code must retain the above copyright notice, this
list of conditions and the following disclaimer.
* Redistributions in binary form must reproduce the above copyright notice,
this list of conditions and the following disclaimer in the documentation
and/or other materials provided with the distribution.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
- Professor Sriraam Natarajan
- Members of the STARAI Lab