https://github.com/srlearn/relationaldatasets.jl

Julia package for fetching and using srlearn-compatible relational datasets.
https://github.com/srlearn/relationaldatasets.jl

datasets inductive-logic-programming relational-learning statistical-relational-learning

Last synced: 4 months ago
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Julia package for fetching and using srlearn-compatible relational datasets.

• Host: GitHub
• URL: https://github.com/srlearn/relationaldatasets.jl
• Owner: srlearn
• License: apache-2.0
• Created: 2021-08-09T02:36:23.000Z (over 4 years ago)
• Default Branch: main
• Last Pushed: 2022-11-03T18:29:07.000Z (over 3 years ago)
• Last Synced: 2025-10-21T12:53:23.426Z (4 months ago)
• Topics: datasets, inductive-logic-programming, relational-learning, statistical-relational-learning
• Language: Julia
• Homepage: https://srlearn.github.io/RelationalDatasets.jl/stable
• Size: 233 KB
• Stars: 2
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
# RelationalDatasets.jl

*A small library for loading and downloading relational datasets.*

or: *The [`relational-datasets`](https://github.com/srlearn/relational-datasets)

Python package—but written in Julia.*

```console

add RelationalDatasets

```

![GitHub release (latest by date)](https://img.shields.io/github/v/release/srlearn/RelationalDatasets.jl)

![GitHub](https://img.shields.io/github/license/srlearn/RelationalDatasets.jl)

[![codecov](https://codecov.io/gh/srlearn/RelationalDatasets.jl/branch/main/graph/badge.svg?token=HaQuwbovLv)](https://codecov.io/gh/srlearn/RelationalDatasets.jl)

[![Ubuntu/macOS/Windows](https://github.com/srlearn/RelationalDatasets.jl/actions/workflows/package-tests.yml/badge.svg)](https://github.com/srlearn/RelationalDatasets.jl/actions/workflows/package-tests.yml)

## Usage

[![RelationalDatasets.jl stable documentation](https://img.shields.io/badge/docs-stable-blue.svg)](https://srlearn.github.io/RelationalDatasets.jl/stable)

[![RelationalDatasets.jl latest documentation](https://img.shields.io/badge/docs-dev-blue.svg)](https://srlearn.github.io/RelationalDatasets.jl/dev)

### Loading and Downloading Benchmark Datasets

`RelationalDatasets.jl` exports a single function: `load` to return train

and test folds.

```julia

using RelationalDatasets

train, test = load("webkb", "v0.0.4", fold=2)

length(train.facts)

# 1344

```

### Converting Vector-based Datasets

*Binary classification when `y` is a vector of 0/1*:

```julia

using RelationalDatasets

data, modes = RelationalDatasets.from_vector(

  [0 1 1; 1 0 2; 2 2 0],

  [0, 0, 1],

)

```

*Regression when `y` is a vector of floats*:

```julia

using RelationalDatasets

data, modes = RelationalDatasets.from_vector(

  [0 1 1; 1 0 2; 2 2 0],

  [1.1, 0.9, 2.5],

)

```

## Install

### From Registry

```bash

add RelationalDatasets

```

### From GitHub

```julia

using Pkg

Pkg.add(url="https://github.com/srlearn/RelationalDatasets.jl")

```