67 lines
1.6 KiB
Rust
67 lines
1.6 KiB
Rust
extern crate openblas_src;
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use kickscore as ks;
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fn main() {
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let mut model = ks::BinaryModel::new(ks::BinaryModelObservation::Probit);
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for player in &["A", "B", "C", "D", "E", "F"] {
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let kernel: Vec<Box<dyn ks::Kernel>> = vec![
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Box::new(ks::kernel::Constant::new(1.0)),
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Box::new(ks::kernel::Matern52::new(0.5, 1.0)),
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];
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model.add_item(player, Box::new(kernel));
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}
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model.observe(&["A"], &["B"], 0.0);
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model.fit();
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for player in &["A", "B", "C", "D", "E", "F"] {
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let (mu, sigma) = model.item_score(player, 1.25);
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println!("{}: mu={} sigma={}", player, mu, sigma);
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}
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model.observe(&["C"], &["D"], 0.25);
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model.fit();
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for player in &["A", "B", "C", "D", "E", "F"] {
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let (mu, sigma) = model.item_score(player, 1.25);
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println!("{}: mu={} sigma={}", player, mu, sigma);
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}
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model.observe(&["E"], &["F"], 0.50);
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model.fit();
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for player in &["A", "B", "C", "D", "E", "F"] {
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let (mu, sigma) = model.item_score(player, 1.25);
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println!("{}: mu={} sigma={}", player, mu, sigma);
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}
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model.observe(&["B"], &["C"], 0.75);
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model.fit();
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for player in &["A", "B", "C", "D", "E", "F"] {
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let (mu, sigma) = model.item_score(player, 1.25);
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println!("{}: mu={} sigma={}", player, mu, sigma);
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}
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model.observe(&["D"], &["E"], 1.00);
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model.fit();
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for player in &["A", "B", "C", "D", "E", "F"] {
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let (mu, sigma) = model.item_score(player, 1.25);
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println!("{}: mu={} sigma={}", player, mu, sigma);
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}
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}
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