TsetlinMachine: A Rust repository from KhaledSharif

Tsetlin Machine implementation in Rust

A "Tsetlin Machine" solves complex pattern recognition problems with easy-to-interpret propositional formulas, and is composed of a collective of Tsetlin Automata. The idea of the machine was proposed in a paper by Ole-Christoffer Granmo.

Running the XOR test

Clone this repository using git clone https://github.com/KhaledSharif/TsetlinMachine.git
Inside the repository root folder, run cargo test
The test will run the XOR example found in tests/xor.rs
The test will only pass if the Tsetlin Machine reaches an accuracy greater than 99% on XOR

Training and testing on MNIST

Get the MNIST data from Kaggle in CSV form
Create a folder called mnist in the same folder that contains src and tests
Copy train.csv and test.csv into the newly created mnist folder
Run cargo run from the repository root folder
Read the code inside src/main.rs to get a better understanding

Example XOR code

let mut tm = tsetlin_machine();
tm.create(2, 2, 10);

let mut rng = thread_rng();
let mut average_error : f32 = 1.0;

for e in 0..1000
{
    let input_vector = &inputs[e % 4];
    {
        let output_vector = tm.activate(input_vector.to_vec());
        let mut correct = false;
        if (input_vector[0] == input_vector[1]) && (!output_vector[0] && output_vector[1])
        {
            correct = true;
        }
        else if output_vector[0] && !output_vector[1]
        {
            correct = true;
        }
        average_error = 0.99 * average_error + 0.01 * (if !correct {1.0} else {0.0});
        println!("{} {} -> {} {} | {}", input_vector[0], input_vector[1], output_vector[0], output_vector[1], average_error);
    }
    tm.learn(&outputs[e % 4], 4.0, 4.0, &mut rng);
}

Example XOR output

true true -> false true   | 0.00007643679
false false -> false true | 0.00007567242
false true -> true false  | 0.0000749157
true false -> true false  | 0.00007416654
true true -> false true   | 0.000073424875

Original implementation