Triazines

libsvm:triazines_scale@1 · Registry 1.2.0. Default version in this registry.

Triazines quantitative structure-activity regression data distributed through the LIBSVM dataset collection, with features scaled to [-1, 1] by the provider.

Dimensions and tasks

Task	Type	Split	Samples	Predictors
default	regression	—	186	60

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

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.

Python

from datamonger import Registry, fetch_data

registry = Registry(
    release="1.2.0",
    index_sha256="4b4e6aeb71ad7e53c3596a725e62008c76c27a59ac68c53a02432898ec8b6f21",
    index_url="https://github.com/jolars/datamonger/releases/download/registry-v1.2.0/index.json",
)
data = fetch_data("libsvm:triazines_scale@1", registry=registry)

R

library(datamonger)

registry <- registry_selector(
  release = "1.2.0",
  index_sha256 = "4b4e6aeb71ad7e53c3596a725e62008c76c27a59ac68c53a02432898ec8b6f21",
  index_url = "https://github.com/jolars/datamonger/releases/download/registry-v1.2.0/index.json"
)
data <- fetch_data("libsvm:triazines_scale@1", registry = registry)

Julia

using Datamonger

registry = registry_selector(
    "1.2.0",
    "4b4e6aeb71ad7e53c3596a725e62008c76c27a59ac68c53a02432898ec8b6f21",
    "https://github.com/jolars/datamonger/releases/download/registry-v1.2.0/index.json",
)
data = fetch_data("libsvm:triazines_scale@1"; registry=registry)

CLI

cat > datamonger-registry.json <<'JSON'
{
  "index_sha256": "4b4e6aeb71ad7e53c3596a725e62008c76c27a59ac68c53a02432898ec8b6f21",
  "index_url": "https://github.com/jolars/datamonger/releases/download/registry-v1.2.0/index.json",
  "release": "1.2.0",
  "schema_version": 1
}
JSON
datamonger --selector datamonger-registry.json fetch 'libsvm:triazines_scale@1'

Representation and variables

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

Component	Kind	Type	Shape
features	sparse_matrix	float64	186 × 60
response	vector	float64	186

Preprocessing

Preprocessing history is not recorded in this registry release.

Provenance and citation

Provider: LIBSVM. Upstream name: triazines_scale. Retrieved: 2026-10-15.

Original source

License

Unknown

The LIBSVM dataset page identifies the source as UCI Qualitative Structure Activity Relationships but provides no license terms for the distributed artifact.

Artifacts

Total download: 62.1 KiB. Sizes describe the distributed files, including any compression.

Artifact	Format	Compression	Size	Distribution	Preservation
data	libsvm	none	62.1 KiB	upstream-only	unknown

data: upstream

Versions in this registry

1 (default)

Registry record

Download the complete registry record, registry selector, or full registry index.

Index SHA-256: 4b4e6aeb71ad7e53c3596a725e62008c76c27a59ac68c53a02432898ec8b6f21.