GitPlanet

Cheap and reliable Node.js hosting starts at $3/month, and $1/month static HTML hosting

Created with love in Canada, visit hostnodejs.com today

Feel like to post an Ad? Learn Details
All Projects → starling-lab → BoostSRL

starling-lab / BoostSRL

Licence: GPL-3.0 license
BoostSRL: "Boosting for Statistical Relational Learning." A gradient-boosting based approach for learning different types of SRL models.

Programming Languages

java
68154 projects - #9 most used programming language

Labels

machine-learningpattern-classificationmachine-learning-algorithmsstatistical-learningartificial-intelligence

Projects that are alternatives of or similar to BoostSRL

Pattern classification
A collection of tutorials and examples for solving and understanding machine learning and pattern classification tasks
Stars: ✭ 3,880 (+12416.13%)
Mutual labels:  pattern-classification, machine-learning-algorithms
Statistical-Learning-using-R
This is a Statistical Learning application which will consist of various Machine Learning algorithms and their implementation in R done by me and their in depth interpretation.Documents and reports related to the below mentioned techniques can be found on my Rpubs profile.
Stars: ✭ 27 (-12.9%)
Mutual labels:  machine-learning-algorithms, statistical-learning
GDLibrary
Matlab library for gradient descent algorithms: Version 1.0.1
Stars: ✭ 50 (+61.29%)
Mutual labels:  machine-learning-algorithms, statistical-learning
AgePredictor
Age classification from text using PAN16, blogs, Fisher Callhome, and Cancer Forum
Stars: ✭ 13 (-58.06%)
Mutual labels:  machine-learning-algorithms
PyLDA
A Latent Dirichlet Allocation implementation in Python.
Stars: ✭ 51 (+64.52%)
Mutual labels:  machine-learning-algorithms
spams-python
A rehost of the python version of SPArse Modeling Software (SPAMS)
Stars: ✭ 28 (-9.68%)
Mutual labels:  machine-learning-algorithms
Intention-Mining-
Intention Mining in Social Networking. It Mines Emotions and polarity for the given keyword . For the keyword it searchers the twitter for the comments and analyzes the results for various events such as Election results, Sports prediction Movie ratings, Breaking news events such as demonetisation and many more. Bayes , Maximum Entropy and Hidde…
Stars: ✭ 19 (-38.71%)
Mutual labels:  machine-learning-algorithms
ml-ai
ML-AI Community | Open Source | Built in Bharat for the World | Data science problem statements and solutions
Stars: ✭ 32 (+3.23%)
Mutual labels:  machine-learning-algorithms
Learn-Machine-Learning-in-3-month
No description or website provided.
Stars: ✭ 35 (+12.9%)
Mutual labels:  machine-learning-algorithms
datascience-mashup
In this repo I will try to gather all of the projects related to data science with clean datasets and high accuracy models to solve real world problems.
Stars: ✭ 36 (+16.13%)
Mutual labels:  machine-learning-algorithms
EXPLORING SKLEARN
Exploring sklearn 🌟
Stars: ✭ 12 (-61.29%)
Mutual labels:  machine-learning-algorithms
lbfgsb-gpu
An open source library for the GPU-implementation of L-BFGS-B algorithm
Stars: ✭ 70 (+125.81%)
Mutual labels:  machine-learning-algorithms
machine-learning-notebooks
🤖 An authorial collection of fundamental python recipes on Machine Learning and Artificial Intelligence.
Stars: ✭ 63 (+103.23%)
Mutual labels:  machine-learning-algorithms
Machine-Learning-Explained
Learn the theory, math and code behind different machine learning algorithms and techniques.
Stars: ✭ 30 (-3.23%)
Mutual labels:  machine-learning-algorithms
RapLyrics-Back
Model training, custom generative function and training for raplyrics.eu - A rap music lyrics generation project
Stars: ✭ 14 (-54.84%)
Mutual labels:  machine-learning-algorithms
bitcoin-prediction
bitcoin prediction algorithms
Stars: ✭ 21 (-32.26%)
Mutual labels:  machine-learning-algorithms
Innovative-Book-Resources
This repository contains books from different topics and perfect enough to give developers a boost in understanding the concepts of Data Science and Artificial Intelligence(other topics are also included but main highlights are these two).
Stars: ✭ 57 (+83.87%)
Mutual labels:  machine-learning-algorithms
pyHSICLasso
Versatile Nonlinear Feature Selection Algorithm for High-dimensional Data
Stars: ✭ 125 (+303.23%)
Mutual labels:  machine-learning-algorithms
Tf-Rec
Tf-Rec is a python💻 package for building⚒ Recommender Systems. It is built on top of Keras and Tensorflow 2 to utilize GPU Acceleration during training.
Stars: ✭ 18 (-41.94%)
Mutual labels:  machine-learning-algorithms
SGDLibrary
MATLAB/Octave library for stochastic optimization algorithms: Version 1.0.20
Stars: ✭ 165 (+432.26%)
Mutual labels:  machine-learning-algorithms
View All Similar Projects ➔

BoostSRL - v1.1

BoostSRL (Boosting for Statistical Relational Models) is a gradient-boosting based approach to learning different types of SRL models.

As with the standard gradient-boosting approach, our approach turns the model-learning problem to learning a sequence of regression models. The key difference to the standard approaches is that we learn relational regression models (i.e. regression models that operate on relational data). We assume the data to be in predicate-logic format and the output are essentially first-order regression trees where the inner nodes contain conjunctions of logical predicates.

Developed by Jude Shavlik, Tushar Khot, Sriraam Natarajan, and members of the StARLinG Lab.

Contact: [email protected]

Latest Release License Wiki Website Downloads Datasets
BoostSRL Wiki Group Website Downloads Datasets

New in Version 1.1

  • Discretization of continuous variables
  • Relational random walks (grounded and lifted)

Getting Started

Prerequisites:

  • Java (tested with openjdk 1.8.0_144)

Installation:

  • Download stable jar file.
  • Download stable source with git.
    git clone -b master https://github.com/boost-starai/BoostSRL.git
  • Nightly builds with git.
    git clone -b development https://github.com/boost-starai/BoostSRL.git

Basic Usage

Basic file structure for the Cora dataset which BoostSRL assumes for most operations.

BoostSRL assumes that data are contained in files with data structured in predicate-logic format.

Positive Examples:

father(harrypotter,jamespotter).
father(ginnyweasley,arthurweasley).
father(ronweasley,arthurweasley).
...

Negative Examples:

father(harrypotter,mollyweasley).
father(harrypotter,lilypotter).
father(harrypotter,ronweasley).
...

Facts:

male(harrypotter).
male(jamespotter).
siblingof(ronweasley,fredweasley).
siblingof(ronweasley,georgeweasley).
childof(jamespotter,harrypotter).
childof(lilypotter,harrypotter).
...

Learning a Relational Dependency Network:

[~/BoostSRL/]$ java -jar v1-0.jar -l -train train/ -target father -trees 10

Inference with the Relational Dependency Network:

[~/BoostSRL/]$ java -jar v1-0.jar -i -model train/models/ -test test/ -target father -trees 10

Contributing

Please refer to CONTRIBUTING.md for documentation on submitting issues and pull requests.

Versioning

We use Semantic Versioning (Major.Minor.Patch) for versioning. See Releases for all stable versions that are available, associated documentation can be found via the changelog.

Acknowledgements

We would like to thank our users, our supporters, and Professor Natarajan.

Note that the project description data, including the texts, logos, images, and/or trademarks, for each open source project belongs to its rightful owner. If you wish to add or remove any projects, please contact us at [email protected].