Function make_multitask_dataset 

pub fn make_multitask_dataset(
    n_samples: usize,
    config: MultiTaskConfig,
) -> Result<MultiTaskDataset>

Generate multi-task learning dataset

Examples found in repository

examples/advanced_generators_demo.rs (line 238)

fn demonstrate_multitask_learning() -> Result<(), Box<dyn std::error::Error>> {
    println!("🎯 MULTI-TASK LEARNING DATASETS");
    println!("{}", "-".repeat(35));

    // Basic multi-task scenario
    println!("Multi-task scenario: Healthcare prediction");
    let config = MultiTaskConfig {
        n_tasks: 4,
        task_types: vec![
            TaskType::Classification(3), // Disease classification
            TaskType::Regression,        // Risk score prediction
            TaskType::Classification(2), // Treatment response
            TaskType::Ordinal(5),        // Severity rating
        ],
        shared_features: 20,        // Common patient features
        task_specific_features: 10, // Task-specific biomarkers
        task_correlation: 0.7,      // High correlation between tasks
        task_noise: vec![0.05, 0.1, 0.08, 0.12],
        random_state: Some(42),
    };

    let multitaskdataset = make_multitask_dataset(1500, config)?;

    println!("  📊 Multi-task dataset structure:");
    println!("    Number of tasks: {}", multitaskdataset.tasks.len());
    println!("    Shared features: {}", multitaskdataset.shared_features);
    println!(
        "    Task correlation: {:.1}",
        multitaskdataset.task_correlation
    );

    for (i, task) in multitaskdataset.tasks.iter().enumerate() {
        println!(
            "    Task {}: {} samples, {} features ({})",
            i + 1,
            task.n_samples(),
            task.n_features(),
            task.metadata
                .get("task_type")
                .unwrap_or(&"unknown".to_string())
        );

        // Analyze task characteristics
        if let Some(target) = &task.target {
            match task
                .metadata
                .get("task_type")
                .map(|s| s.as_str())
                .unwrap_or("unknown")
            {
                "classification" => {
                    let n_classes = analyze_classification_target(target);
                    println!("      Classes: {n_classes}");
                }
                "regression" => {
                    let (mean, std) = analyze_regression_target(target);
                    println!("      Target range: {mean:.2} ± {std:.2}");
                }
                "ordinal_regression" => {
                    let levels = analyze_ordinal_target(target);
                    println!("      Ordinal levels: {levels}");
                }
                _ => {}
            }
        }
    }

    // Transfer learning scenario
    println!("\nTransfer learning analysis:");
    analyze_task_relationships(&multitaskdataset);

    println!();
    Ok(())
}