DARJEELING

Machine learning tools for Rust

Installation

Add the following to your Cargo.toml file darjeeling = "0.1.0"

Example

``` use darjeeling::{neural_network::NeuralNetwork, input::Input}; use std::io::{BufReader, BufRead}; use std::fs;

fn main() { trainnetworkxor(1.0); }

// Create data, categories, and a network for models to be trained on pub fn trainnetworkxor(learningrate: f32) { let categories = vec![String::from("1"), String::from("0")]; let mut data = xorfile(); let mut net = NeuralNetwork::new(2, 2, 2, 1, false); net.learn(&mut data, categories, learning_rate); }

// Read the file you want to and format it as Inputs fn xor_file() -> Vec { let file = match fs::File::open("xor.txt") { Ok(file) => file, Err(error) => panic!("Panic opening the file: {:?}", error) };

let reader = BufReader::new(file); let mut inputs: Vec = vec![];

for l in reader.lines() {

  let line = match l {
      Ok(line) => line,
      Err(error) => panic!("{:?}", error)
  };

  let init_inputs: Vec<&str> = line.split(";").collect();
  let mut float_inputs: Vec<f32> = vec![init_inputs[0].split(" ").collect::<Vec<&str>>()[0].parse().unwrap(), init_inputs[0].split(" ").collect::<Vec<&str>>()[1].parse().unwrap()];

  let input: Input = Input { inputs: float_inputs, answer:init_inputs.get(init_inputs.len()-1).as_ref().unwrap().to_owned().to_string() };
  inputs.push(input);

}

inputs
} ```