Module: `aprender::datasets`

Public module of the aprender-core crate.

use aprender::datasets::{load_iris, make_blobs};
// See `cargo doc -p aprender-core --open` for full API reference.

Module summary

aprender::datasets provides the dataset generators and loaders that Pillar 1 (replace and beat scikit-learn) measures against. It mirrors sklearn.datasets:

function	mirrors
`make_blobs`	`sklearn.datasets.make_blobs`
`make_regression`	`sklearn.datasets.make_regression`
`make_classification`	`sklearn.datasets.make_classification`
`load_iris`	`sklearn.datasets.load_iris`

The embedded real data — currently Iris — is sourced once from scikit-learn and committed to the repository, so loading it has no runtime Python or network dependency. That property is what lets the beat benchmarks in contracts/beat-sklearn-*.yaml compare like against like without a Python process in the loop.

Larger embedded sets (load_digits, load_california_housing) are not implemented yet; they are tracked as a continuation of PMAT-720. This chapter says so rather than implying a completeness the module does not have.

Aprender — Pure Rust ML Framework

Module: `aprender::datasets`

Source

Example

Module summary

See also

Aprender — Pure Rust ML Framework

Module: aprender::datasets

Source

Example

Module summary

See also

Module: `aprender::datasets`