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Aug 27, 2021
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README from_vector notes and documentation links #12

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aab6ab2
📝 Add further usage and doc links to README
hayesall Aug 27, 2021
403cce1
🔖 Bump version number in `Project.toml`
hayesall Aug 27, 2021
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2 changes: 1 addition & 1 deletion Project.toml
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Original file line number Diff line number Diff line change
Expand Up @@ -2,7 +2,7 @@ name = "RelationalDatasets"
uuid = "6b8bdb16-f930-11eb-22b5-7ba1dabdf7a8"
license = "Apache 2.0"
authors = ["Alexander L. Hayes <[email protected]>"]
version = "0.1.1"
version = "0.2.0"

[deps]
HTTP = "cd3eb016-35fb-5094-929b-558a96fad6f3"
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46 changes: 38 additions & 8 deletions README.md
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@@ -1,11 +1,13 @@
# 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.*
*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)
Expand All @@ -14,18 +16,46 @@

## 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)

println(length(train.facts))
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
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