add first example

Cargo.toml

@@ -24,6 +24,6 @@ opt-level = 0
 [profile.release]
 opt-level = 3
 
-[[bench]]
+[[example]]
 name = "credit_card"
-harness = false
+path = "examples/anomaly_detection/credit_card.rs"

README.md

@@ -1,4 +1,4 @@
-<h1>🦀 LightRiver • fast online machine learning</h1>
+<h1>🦀 LightRiver • fast and simple online machine learning</h1>
 
 <p>
 
@@ -25,12 +25,34 @@
   <img src="https://github.com/online-ml/light-river/assets/8095957/fc8ea218-62f9-4643-b25d-f9265ef962f8" width="25%" align="right" />
 </div>
 
-LightRiver is an online machine learning library written in Rust. It is meant to be used in high-throughput environments, as well as TinyML systems.
+Reed is an online machine learning library written in Rust. It is meant to be used in high-throughput environments, as well as TinyML systems.
 
 This library is complementary to [River](https://github.com/online-ml/river/). The latter provides a wide array of online methods, but is not ideal when it comes to performance. The idea is to take the algorithms that work best in River, and implement them in a way that is more performant. As such, LightRiver is not meant to be a general purpose library. It is meant to be a fast online machine learning library that provides a few algorithms that are known to work well in online settings. This is a akin to the way [scikit-learn](https://scikit-learn.org/) and [LightGBM](https://lightgbm.readthedocs.io/en/stable/) are complementary to each other.
 
+## 🧑‍💻 Usage
+
+### 🚨 Anomaly detection
+
+```sh
+cargo run --release --example credit_card
+```
+
+### 📈 Regression
+
+🏗️ We plan to implement Aggregated Mondrian Forests.
+
+### 📊 Classification
+
+🏗️ We plan to implement Aggregated Mondrian Forests.
+
+### 🛒 Recsys
+
+🏗️ [Vowpal Wabbit](https://vowpalwabbit.org/) is very good at recsys via contextual bandits. We don't plan to compete with it. Eventually we want to research a tree-based contextual bandit.
+
 ## 🚀 Performance
 
+TODO: add a `benches` directory
+
 ## 📝 License
 
 LightRiver is free and open-source software licensed under the [3-clause BSD license](LICENSE).

examples/anomaly_detection/credit_card.rs

@@ -0,0 +1,25 @@
+use light_river::anomaly::half_space_tree::HalfSpaceTree;
+use light_river::datasets::credit_card::CreditCard;
+use std::time::Instant;
+
+fn main() {
+    let now = Instant::now();
+
+    // PARAMETERS
+    let window_size: u32 = 1000;
+    let n_trees: u32 = 50;
+    let height: u32 = 6;
+
+    // INITIALIZATION
+    let mut hst = HalfSpaceTree::new(window_size, n_trees, height, None);
+
+    // LOOP
+    let transactions = CreditCard::load_credit_card_transactions().unwrap();
+    for transaction in transactions {
+        let observation = transaction.unwrap().get_observation();
+        let _ = hst.update(&observation, true, true);
+    }
+
+    let elapsed_time = now.elapsed();
+    println!("Took {}ms", elapsed_time.as_millis());
+}

src/anomaly/half_space_tree.rs

@@ -8,11 +8,13 @@ use std::mem;
 use crate::common::Observation;
 
 // Return the index of a node's left child node.
+#[inline]
 fn left_child(node: u32) -> u32 {
     node * 2 + 1
 }
 
 // Return the index of a node's right child node.
+#[inline]
 fn right_child(node: u32) -> u32 {
     node * 2 + 2
 }