| <!DOCTYPE html><html lang="en"><head><meta charset="utf-8"><meta name="viewport" content="width=device-width, initial-scale=1.0"><meta name="generator" content="rustdoc"><meta name="description" content="Source of the Rust file `/root/.cargo/registry/src/github.com-1ecc6299db9ec823/gbdt-0.1.1/src/lib.rs`."><meta name="keywords" content="rust, rustlang, rust-lang"><title>lib.rs - source</title><link rel="preload" as="font" type="font/woff2" crossorigin href="../../SourceSerif4-Regular.ttf.woff2"><link rel="preload" as="font" type="font/woff2" crossorigin href="../../FiraSans-Regular.woff2"><link rel="preload" as="font" type="font/woff2" crossorigin href="../../FiraSans-Medium.woff2"><link rel="preload" as="font" type="font/woff2" crossorigin href="../../SourceCodePro-Regular.ttf.woff2"><link rel="preload" as="font" type="font/woff2" crossorigin href="../../SourceSerif4-Bold.ttf.woff2"><link rel="preload" as="font" type="font/woff2" crossorigin href="../../SourceCodePro-Semibold.ttf.woff2"><link rel="stylesheet" href="../../normalize.css"><link rel="stylesheet" href="../../rustdoc.css" id="mainThemeStyle"><link rel="stylesheet" href="../../ayu.css" disabled><link rel="stylesheet" href="../../dark.css" disabled><link rel="stylesheet" href="../../light.css" id="themeStyle"><script id="default-settings" ></script><script src="../../storage.js"></script><script defer src="../../source-script.js"></script><script defer src="../../source-files.js"></script><script defer src="../../main.js"></script><noscript><link rel="stylesheet" href="../../noscript.css"></noscript><link rel="alternate icon" type="image/png" href="../../favicon-16x16.png"><link rel="alternate icon" type="image/png" href="../../favicon-32x32.png"><link rel="icon" type="image/svg+xml" href="../../favicon.svg"></head><body class="rustdoc source"><!--[if lte IE 11]><div class="warning">This old browser is unsupported and will most likely display funky things.</div><![endif]--><nav class="sidebar"><a class="sidebar-logo" href="../../gbdt/index.html"><div class="logo-container"><img class="rust-logo" src="../../rust-logo.svg" alt="logo"></div></a></nav><main><div class="width-limiter"><nav class="sub"><a class="sub-logo-container" href="../../gbdt/index.html"><img class="rust-logo" src="../../rust-logo.svg" alt="logo"></a><form class="search-form"><div class="search-container"><span></span><input class="search-input" name="search" autocomplete="off" spellcheck="false" placeholder="Click or press ‘S’ to search, ‘?’ for more options…" type="search"><div id="help-button" title="help" tabindex="-1"><a href="../../help.html">?</a></div><div id="settings-menu" tabindex="-1"><a href="../../settings.html" title="settings"><img width="22" height="22" alt="Change settings" src="../../wheel.svg"></a></div></div></form></nav><section id="main-content" class="content"><div class="example-wrap"><pre class="src-line-numbers"><span id="1">1</span> |
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| </pre><pre class="rust"><code><span class="comment">//Copyright (C) 2017-2018 Baidu, Inc. All Rights Reserved. |
| // |
| //Redistribution and use in source and binary forms, with or without |
| //modification, are permitted provided that the following conditions |
| //are met: |
| // |
| // * Redistributions of source code must retain the above copyright |
| // notice, this list of conditions and the following disclaimer. |
| // |
| // * Redistributions in binary form must reproduce the above copyright |
| // notice, this list of conditions and the following disclaimer in |
| // the documentation and/or other materials provided with the |
| // distribution. |
| // |
| // * Neither the name of Baidu, Inc., nor the names of its |
| // contributors may be used to endorse or promote products derived |
| // from this software without specific prior written permission. |
| // |
| //THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS |
| //"AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT |
| //LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR |
| //A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT |
| //OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, |
| //SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT |
| //LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; Loss OF USE, |
| //DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY |
| //THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT |
| //(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE |
| //OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. |
| |
| </span><span class="attribute">#![allow(clippy::ptr_arg)] |
| #![allow(clippy::type_complexity)] |
| |
| #![cfg_attr(all(feature = <span class="string">"mesalock_sgx"</span>, |
| not(target_env = <span class="string">"sgx"</span>)), no_std)] |
| #![cfg_attr(all(target_env = <span class="string">"sgx"</span>, target_vendor = <span class="string">"mesalock"</span>), feature(rustc_private))] |
| |
| #[cfg(all(feature = <span class="string">"mesalock_sgx"</span>, not(target_env = <span class="string">"sgx"</span>)))] |
| #[macro_use] |
| </span><span class="kw">extern crate </span>sgx_tstd <span class="kw">as </span>std; |
| |
| <span class="kw">pub mod </span>binary_tree; |
| <span class="kw">pub mod </span>config; |
| <span class="kw">pub mod </span>decision_tree; |
| <span class="kw">pub mod </span>fitness; |
| <span class="kw">pub mod </span>gradient_boost; |
| |
| <span class="attribute">#[cfg(feature = <span class="string">"input"</span>)] |
| #[macro_use] |
| </span><span class="kw">extern crate </span>cfg_if; |
| |
| <span class="comment">// Input heavily depends on I/O and may not be required in SGX |
| </span><span class="attribute">#[cfg(feature = <span class="string">"input"</span>)] |
| </span><span class="kw">pub mod </span>input; |
| |
| |
| <span class="attribute">#[cfg(test)] |
| </span><span class="kw">mod </span>tests { |
| |
| <span class="attribute">#[test] |
| </span><span class="kw">fn </span>walk_tree() { |
| <span class="kw">use </span><span class="kw">crate</span>::binary_tree::<span class="kw-2">*</span>; |
| <span class="kw">let </span><span class="kw-2">mut </span>tree: BinaryTree<f32> = BinaryTree::new(); |
| <span class="kw">let </span>root = BinaryTreeNode::new(<span class="number">10.0</span>); |
| |
| <span class="kw">let </span>root_index = tree.add_root(root); |
| |
| <span class="kw">let </span>n1 = BinaryTreeNode::new(<span class="number">5.0</span>); |
| <span class="kw">let </span>n2 = BinaryTreeNode::new(<span class="number">6.0</span>); |
| |
| <span class="kw">let </span>n1_index = tree.add_left_node(root_index, n1); |
| <span class="kw">let </span>n2_index = tree.add_right_node(root_index, n2); |
| |
| <span class="kw">let </span>n3 = BinaryTreeNode::new(<span class="number">7.0</span>); |
| <span class="kw">let </span>n4 = BinaryTreeNode::new(<span class="number">8.0</span>); |
| |
| tree.add_left_node(n2_index, n3); |
| tree.add_right_node(n2_index, n4); |
| |
| <span class="kw">let </span>n5 = BinaryTreeNode::new(<span class="number">9.0</span>); |
| |
| tree.add_left_node(n1_index, n5); |
| |
| tree.print(); |
| } |
| |
| <span class="attribute">#[test] |
| </span><span class="kw">fn </span>decision_tree() { |
| <span class="kw">use </span><span class="kw">crate</span>::config::Loss; |
| <span class="kw">use </span><span class="kw">crate</span>::decision_tree::<span class="kw-2">*</span>; |
| <span class="kw">let </span><span class="kw-2">mut </span>tree = DecisionTree::new(); |
| tree.set_feature_size(<span class="number">3</span>); |
| tree.set_max_depth(<span class="number">2</span>); |
| tree.set_min_leaf_size(<span class="number">1</span>); |
| tree.set_loss(Loss::SquaredError); |
| <span class="kw">let </span>data1 = Data { |
| feature: <span class="macro">vec!</span>[<span class="number">1.0</span>, <span class="number">2.0</span>, <span class="number">3.0</span>], |
| target: <span class="number">2.0</span>, |
| weight: <span class="number">1.0</span>, |
| label: <span class="number">1.0</span>, |
| residual: <span class="number">1.0</span>, |
| initial_guess: <span class="number">1.0</span>, |
| }; |
| <span class="kw">let </span>data2 = Data { |
| feature: <span class="macro">vec!</span>[<span class="number">1.1</span>, <span class="number">2.1</span>, <span class="number">3.1</span>], |
| target: <span class="number">1.0</span>, |
| weight: <span class="number">1.0</span>, |
| label: <span class="number">1.0</span>, |
| residual: <span class="number">1.0</span>, |
| initial_guess: <span class="number">1.0</span>, |
| }; |
| <span class="kw">let </span>data3 = Data { |
| feature: <span class="macro">vec!</span>[<span class="number">2.0</span>, <span class="number">2.0</span>, <span class="number">1.0</span>], |
| target: <span class="number">0.5</span>, |
| weight: <span class="number">1.0</span>, |
| label: <span class="number">2.0</span>, |
| residual: <span class="number">2.0</span>, |
| initial_guess: <span class="number">2.0</span>, |
| }; |
| <span class="kw">let </span>data4 = Data { |
| feature: <span class="macro">vec!</span>[<span class="number">2.0</span>, <span class="number">2.3</span>, <span class="number">1.2</span>], |
| target: <span class="number">3.0</span>, |
| weight: <span class="number">1.0</span>, |
| label: <span class="number">0.0</span>, |
| residual: <span class="number">0.0</span>, |
| initial_guess: <span class="number">1.0</span>, |
| }; |
| |
| <span class="kw">let </span><span class="kw-2">mut </span>dv = Vec::new(); |
| dv.push(data1.clone()); |
| dv.push(data2.clone()); |
| dv.push(data3.clone()); |
| dv.push(data4.clone()); |
| |
| <span class="kw">let </span><span class="kw-2">mut </span>cache = TrainingCache::get_cache(<span class="number">3</span>, <span class="kw-2">&</span>dv, <span class="number">3</span>); |
| tree.fit(<span class="kw-2">&</span>dv, <span class="kw-2">&mut </span>cache); |
| |
| tree.print(); |
| |
| <span class="kw">let </span><span class="kw-2">mut </span>dv = Vec::new(); |
| dv.push(data1.clone()); |
| dv.push(data2.clone()); |
| dv.push(data3.clone()); |
| dv.push(data4.clone()); |
| |
| <span class="macro">println!</span>(<span class="string">"{:?}"</span>, tree.predict(<span class="kw-2">&</span>dv)); |
| } |
| |
| <span class="attribute">#[test] |
| </span><span class="kw">fn </span>build_decision_tree() { |
| <span class="kw">use </span><span class="kw">crate</span>::decision_tree::DecisionTree; |
| <span class="kw">let _ </span>= DecisionTree::new(); |
| } |
| |
| <span class="attribute">#[test] |
| </span><span class="kw">fn </span>config_express() { |
| <span class="kw">use </span><span class="kw">crate</span>::config::Config; |
| <span class="kw">let </span>c = Config::new(); |
| <span class="macro">println!</span>(<span class="string">"{}"</span>, c.to_string()); |
| } |
| |
| <span class="attribute">#[test] |
| </span><span class="kw">fn </span>loss_type() { |
| <span class="kw">use </span><span class="kw">crate</span>::config::{loss2string, string2loss, Loss}; |
| <span class="macro">assert_eq!</span>(string2loss(<span class="string">"SquaredError"</span>), Loss::SquaredError); |
| <span class="macro">assert_eq!</span>(string2loss(<span class="string">"LogLikelyhood"</span>), Loss::LogLikelyhood); |
| <span class="macro">assert_eq!</span>(string2loss(<span class="string">"LAD"</span>), Loss::LAD); |
| |
| <span class="macro">assert_eq!</span>(loss2string(<span class="kw-2">&</span>Loss::SquaredError), <span class="string">"SquaredError"</span>); |
| <span class="macro">assert_eq!</span>(loss2string(<span class="kw-2">&</span>Loss::LogLikelyhood), <span class="string">"LogLikelyhood"</span>); |
| <span class="macro">assert_eq!</span>(loss2string(<span class="kw-2">&</span>Loss::LAD), <span class="string">"LAD"</span>); |
| } |
| |
| <span class="attribute">#[test] |
| </span><span class="kw">fn </span>fitness() { |
| <span class="kw">use </span><span class="kw">crate</span>::decision_tree::<span class="kw-2">*</span>; |
| <span class="kw">let </span><span class="kw-2">mut </span>dv: DataVec = Vec::new(); |
| dv.push(Data { |
| feature: Vec::new(), |
| target: <span class="number">1.0</span>, |
| weight: <span class="number">0.1</span>, |
| label: <span class="number">1.0</span>, |
| residual: <span class="number">0.5</span>, |
| initial_guess: VALUE_TYPE_UNKNOWN, |
| }); |
| dv.push(Data { |
| feature: Vec::new(), |
| target: <span class="number">1.0</span>, |
| weight: <span class="number">0.2</span>, |
| label: <span class="number">0.0</span>, |
| residual: <span class="number">0.5</span>, |
| initial_guess: VALUE_TYPE_UNKNOWN, |
| }); |
| dv.push(Data { |
| feature: Vec::new(), |
| target: <span class="number">0.0</span>, |
| weight: <span class="number">0.3</span>, |
| label: <span class="number">1.0</span>, |
| residual: <span class="number">0.5</span>, |
| initial_guess: VALUE_TYPE_UNKNOWN, |
| }); |
| dv.push(Data { |
| feature: Vec::new(), |
| target: <span class="number">0.0</span>, |
| weight: <span class="number">0.4</span>, |
| label: <span class="number">0.0</span>, |
| residual: <span class="number">0.5</span>, |
| initial_guess: VALUE_TYPE_UNKNOWN, |
| }); |
| |
| <span class="kw">use </span><span class="kw">crate</span>::fitness::{ |
| almost_equal, average, label_average, same, weighted_label_median, |
| weighted_residual_median, |
| }; |
| <span class="macro">assert_eq!</span>(<span class="bool-val">true</span>, almost_equal(<span class="number">0.1</span>, <span class="number">0.100000000001</span>)); |
| <span class="macro">assert_eq!</span>(<span class="bool-val">false</span>, same(<span class="kw-2">&</span>dv, dv.len())); |
| <span class="macro">assert!</span>(almost_equal(<span class="number">0.3</span>, average(<span class="kw-2">&</span>dv, dv.len()))); |
| <span class="macro">assert!</span>(almost_equal(<span class="number">0.4</span>, label_average(<span class="kw-2">&</span>dv, dv.len()))); |
| <span class="macro">assert!</span>(almost_equal(<span class="number">0.0</span>, weighted_label_median(<span class="kw-2">&</span>dv, dv.len()))); |
| <span class="macro">assert!</span>(almost_equal(<span class="number">0.5</span>, weighted_residual_median(<span class="kw-2">&</span>dv, dv.len()))); |
| } |
| } |
| </code></pre></div> |
| </section></div></main><div id="rustdoc-vars" data-root-path="../../" data-current-crate="gbdt" data-themes="ayu,dark,light" data-resource-suffix="" data-rustdoc-version="1.66.0-nightly (5c8bff74b 2022-10-21)" ></div></body></html> |
