# RCV1 Binary

[Browse datasets](<../../>) 

`libsvm:rcv1-binary@1` · Registry `1.3.0`. Default version in this registry. 

LIBSVM's binary classification variant of Reuters Corpus Volume 1, with 47,236 sparse text features and predefined training and test sets. Positive labels combine CCAT and ECAT, and negative labels combine GCAT and MCAT. Documents assigned to both groups are removed. The provider's feature values, labels, splits, and row order are preserved. 

<a id="dimensions-and-tasks"></a>

## Dimensions and tasks

| Task | Type | Split | Samples | Predictors |
| --- | --- | --- | --- | --- |
| default | classification | test | 677,399 | 47,236 |
| default | classification | train | 20,242 | 47,236 |

Predictor counts follow each task's feature selection and exclude targets and identifiers. Sample counts are reported separately for each split. 

<a id="retrieve"></a>

## Retrieve

These examples pin both the dataset version and the registry's exact index. An uncached dataset requires network access to its source. The CLI retrieves verified artifacts. The language clients also decode them. 

<a id="python"></a>

### Python

```python
from datamonger import Registry, fetch_data

registry = Registry(
    release="1.3.0",
    index_sha256="94639f8d711d64895689d6da87add0f0f56574070262ec2a04f1f1ad43279f85",
    index_url="https://github.com/jolars/datamonger/releases/download/registry-v1.3.0/index.json",
)
data = fetch_data("libsvm:rcv1-binary@1", registry=registry)
```

<a id="r"></a>

### R

```r
library(datamonger)

registry <- registry_selector(
  release = "1.3.0",
  index_sha256 = "94639f8d711d64895689d6da87add0f0f56574070262ec2a04f1f1ad43279f85",
  index_url = "https://github.com/jolars/datamonger/releases/download/registry-v1.3.0/index.json"
)
data <- fetch_data("libsvm:rcv1-binary@1", registry = registry)
```

<a id="julia"></a>

### Julia

```julia
using Datamonger

registry = registry_selector(
    "1.3.0",
    "94639f8d711d64895689d6da87add0f0f56574070262ec2a04f1f1ad43279f85",
    "https://github.com/jolars/datamonger/releases/download/registry-v1.3.0/index.json",
)
data = fetch_data("libsvm:rcv1-binary@1"; registry=registry)
```

<a id="cli"></a>

### CLI

```sh
cat > datamonger-registry.json <<'JSON'
{
  "index_sha256": "94639f8d711d64895689d6da87add0f0f56574070262ec2a04f1f1ad43279f85",
  "index_url": "https://github.com/jolars/datamonger/releases/download/registry-v1.3.0/index.json",
  "release": "1.3.0",
  "schema_version": 1
}
JSON
datamonger --selector datamonger-registry.json fetch 'libsvm:rcv1-binary@1'
```

<a id="representation-and-variables"></a>

## Representation and variables

Tabular data with a sparse representation. Decoder: `libsvm-split` version 1. 

| Component | Kind | Type | Shape |
| --- | --- | --- | --- |
| train\_features | sparse\_matrix | float64 | 20,242 × 47,236 |
| train\_response | vector | int64 | 20,242 |
| test\_features | sparse\_matrix | float64 | 677,399 × 47,236 |
| test\_response | vector | int64 | 677,399 |

<a id="preprocessing"></a>

## Preprocessing

<a id="upstream"></a>

### Upstream

Status: documented. 

The provider feature values, labels, splits, and row order are preserved. Earlier text feature preparation is not described here. 

**response-dichotomization.** Combine CCAT and ECAT into the positive class and GCAT and MCAT into the negative class. 

Parameters: negative\_classes: GCAT, MCAT; positive\_classes: CCAT, ECAT. 

**sample-selection.** Remove documents assigned to both the positive and negative groups. 

Parameters: predicate: retain documents assigned to only one label group. 

Evidence: [https://www.csie.ntu.edu.tw/~cjlin/libsvmtools/datasets/binary.html\#rcv1.binary](<https://www.csie.ntu.edu.tw/~cjlin/libsvmtools/datasets/binary.html#rcv1.binary>) 

<a id="datamonger"></a>

### Datamonger

Status: none. 

Datamonger decodes the provider artifacts without additional statistical preprocessing. 

Evidence: spec/decoders/libsvm-v1.md 

<a id="provenance-and-citation"></a>

## Provenance and citation

Provider: LIBSVM. Upstream name: rcv1.binary. Retrieved: 2026-10-19. 

[Original source](<https://www.csie.ntu.edu.tw/~cjlin/libsvmtools/datasets/binary.html#rcv1.binary>) 

Authors: David D. Lewis, Yiming Yang, Tony G. Rose, Fan Li. 

David D. Lewis, Yiming Yang, Tony G. Rose, and Fan Li. RCV1: A New Benchmark Collection for Text Categorization Research. Journal of Machine Learning Research, 5:361-397, 2004. [https://www.jmlr.org/papers/v5/lewis04a.html](<https://www.jmlr.org/papers/v5/lewis04a.html>) 

<a id="license"></a>

## License

Unknown 

[License information](<https://trec.nist.gov/data/reuters/reuters.html>) 

The LIBSVM dataset page documents the source and binary label mapping but provides no license terms for these artifacts. NIST identifies Reuters copyright and organizational and individual agreements for the source corpus. No license or redistribution grant has been established for the LIBSVM transformation. 

<a id="artifacts"></a>

## Artifacts

Total download: 445.4 MiB. Sizes describe the distributed files, including any compression. 

| Artifact | Format | Compression | Size | Distribution | Preservation |
| --- | --- | --- | --- | --- | --- |
| train | libsvm | bzip2 | 13.1 MiB | upstream-only | unknown |
| test | libsvm | bzip2 | 432.3 MiB | upstream-only | unknown |

[train: upstream](<https://www.csie.ntu.edu.tw/~cjlin/libsvmtools/datasets/binary/rcv1_train.binary.bz2>) 

[test: upstream](<https://www.csie.ntu.edu.tw/~cjlin/libsvmtools/datasets/binary/rcv1_test.binary.bz2>) 

<a id="versions-in-this-registry"></a>

## Versions in this registry

[1](<1>) (default) 

<a id="registry-record"></a>

## Registry record

Download the [complete registry record](<../../../assets/1252a0ed9a875ab6715846adcb67e7f67014a79087c422286f5e51456eec52df.bin>), [registry selector](<../../../assets/aab75a78e13dc82828a91a7f0399fbe2550941fd4944b2dc669a80fe88adadbf.bin>), or [full registry index](<https://github.com/jolars/datamonger/releases/download/registry-v1.3.0/index.json>). 

Index SHA-256: `94639f8d711d64895689d6da87add0f0f56574070262ec2a04f1f1ad43279f85`.