random-forests

A Rust library for Random Forests.

Support for generic impurity measures:

• [x] Entropy
• [x] Gini

installation

Add to your Cargo.toml:

randomforests = "*"

usage

Add the crate and RandomForests to your code:

extern crate randomforests;

use randomforests::RandomForest;

Create a Dataset as collection of Items:

let mut dataset = Dataset::new();
let mut item1 = Item::new();
item1.insert("lang".to_string(), Value { data: "rust".to_string() });
item1.insert("typing".to_string(), Value { data: "static".to_string() });
dataset.push(item1);

let mut item2 = Item::new();
item2.insert("lang".to_string(), Value { data: "python".to_string() } );
item2.insert("typing".to_string(), Value { data: "dynamic".to_string() } );
dataset.push(item2);

let mut item3 = Item::new();
item3.insert("lang".to_string(), Value { data: "haskell".to_string() });
item3.insert("typing".to_string(), Value { data: "static".to_string() });
dataset.push(item3);

Initialise the classifier and train it classifier by passing the Dataset, a TreeConfig, the number of trees and the data subsample size:

let mut config = TreeConfig::new();
config.decision = "lang".to_string();
let forest = RandomForest::build("lang".to_string(), config, &dataset, 100, 3);

Create a question as an Item:

let mut question = Item::new();
question.insert("typing".to_string(), Value { data: "static".to_string() });

And get the predictions:

let answer = RandomForest::predict(forest, question);
// answer = {Value { data: haskell }: 48, Value { data: rust }: 52}