6f22bbd150
* chore: fix clippy lints --------- Co-authored-by: Luis Moreno <morenol@users.noreply.github.com>
86 lines
2.6 KiB
Rust
86 lines
2.6 KiB
Rust
//! # The Iris flower dataset
|
|
//!
|
|
//! | Number of Instances | Number of Attributes | Missing Values? | Associated Tasks: |
|
|
//! |-|-|-|-|
|
|
//! | 150 | 4 | No | Classification |
|
|
//!
|
|
//! [Fisher's Iris dataset](https://archive.ics.uci.edu/ml/datasets/iris) is a multivariate dataset that was published in 1936 by Ronald Fisher.
|
|
//! This multivariate dataset is frequently used to demonstrate various machine learning algorithms. The dataset has following attributes:
|
|
//!
|
|
//! | Predictor | Data Type | Target? |
|
|
//! |-|-|-|
|
|
//! | Sepal length | Numerical | No |
|
|
//! | Sepal width | Numerical | No |
|
|
//! | Petal length | Numerical | No |
|
|
//! | Petal width | Numerical | No |
|
|
//! | Class | Nominal | Yes |
|
|
//!
|
|
use crate::dataset::deserialize_data;
|
|
use crate::dataset::Dataset;
|
|
|
|
/// Get dataset
|
|
pub fn load_dataset() -> Dataset<f32, u32> {
|
|
let (x, y, num_samples, num_features): (Vec<f32>, Vec<u32>, usize, usize) =
|
|
match deserialize_data(std::include_bytes!("iris.xy")) {
|
|
Err(why) => panic!("Can't deserialize iris.xy. {why}"),
|
|
Ok((x, y, num_samples, num_features)) => (
|
|
x,
|
|
y.into_iter().map(|x| x as u32).collect(),
|
|
num_samples,
|
|
num_features,
|
|
),
|
|
};
|
|
|
|
Dataset {
|
|
data: x,
|
|
target: y,
|
|
num_samples,
|
|
num_features,
|
|
feature_names: [
|
|
"sepal length (cm)",
|
|
"sepal width (cm)",
|
|
"petal length (cm)",
|
|
"petal width (cm)",
|
|
]
|
|
.iter()
|
|
.map(|s| s.to_string())
|
|
.collect(),
|
|
target_names: ["setosa", "versicolor", "virginica"]
|
|
.iter()
|
|
.map(|s| s.to_string())
|
|
.collect(),
|
|
description: "Iris dataset: https://archive.ics.uci.edu/ml/datasets/iris".to_string(),
|
|
}
|
|
}
|
|
|
|
#[cfg(test)]
|
|
mod tests {
|
|
|
|
// #[cfg(not(target_arch = "wasm32"))]
|
|
// use super::super::*;
|
|
use super::*;
|
|
|
|
// TODO: fix serialization
|
|
// #[cfg(not(target_arch = "wasm32"))]
|
|
// #[test]
|
|
// #[ignore]
|
|
// fn refresh_iris_dataset() {
|
|
// // run this test to generate iris.xy file.
|
|
// let dataset = load_dataset();
|
|
// assert!(serialize_data(&dataset, "iris.xy").is_ok());
|
|
// }
|
|
|
|
#[cfg_attr(
|
|
all(target_arch = "wasm32", not(target_os = "wasi")),
|
|
wasm_bindgen_test::wasm_bindgen_test
|
|
)]
|
|
#[test]
|
|
fn iris_dataset() {
|
|
let dataset = load_dataset();
|
|
assert_eq!(dataset.data.len(), 50 * 3 * 4);
|
|
assert_eq!(dataset.target.len(), 50 * 3);
|
|
assert_eq!(dataset.num_features, 4);
|
|
assert_eq!(dataset.num_samples, 50 * 3);
|
|
}
|
|
}
|