Struct lightgbm::Dataset

pub struct Dataset { /* fields omitted */ }

Dataset used throughout LightGBM for training.

Examples

from mat

use lightgbm::Dataset;

let data = vec![vec![1.0, 0.1, 0.2, 0.1],
               vec![0.7, 0.4, 0.5, 0.1],
               vec![0.9, 0.8, 0.5, 0.1],
               vec![0.2, 0.2, 0.8, 0.7],
               vec![0.1, 0.7, 1.0, 0.9]];
let label = vec![0.0, 0.0, 0.0, 1.0, 1.0];
let dataset = Dataset::from_mat(data, label).unwrap();

from file

use lightgbm::Dataset;

let dataset = Dataset::from_file(&"lightgbm-sys/lightgbm/examples/binary_classification/binary.train").unwrap();

Implementations

impl Dataset

pub fn from_mat(data: Vec<Vec<f64>>, label: Vec<f32>) -> Result<Self>

Create a new Dataset from dense array in row-major order.

Example

use lightgbm::Dataset;

let data = vec![vec![1.0, 0.1, 0.2, 0.1],
               vec![0.7, 0.4, 0.5, 0.1],
               vec![0.9, 0.8, 0.5, 0.1],
               vec![0.2, 0.2, 0.8, 0.7],
               vec![0.1, 0.7, 1.0, 0.9]];
let label = vec![0.0, 0.0, 0.0, 1.0, 1.0];
let dataset = Dataset::from_mat(data, label).unwrap();

pub fn from_file(file_path: &str) -> Result<Self>

Create a new Dataset from file.

file is tsv.

<label>\t<value>\t<value>\t...

2 0.11 0.89 0.2
3 0.39 0.1 0.4
0 0.1 0.9 1.0

Example

use lightgbm::Dataset;

let dataset = Dataset::from_file(&"lightgbm-sys/lightgbm/examples/binary_classification/binary.train");

Trait Implementations

impl Drop for Dataset

fn drop(&mut self)

Executes the destructor for this type.