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MLTA

Machine Learning Test Analyzer and recorder

Overview

Purpose

To aid developers using machine learning algorithms in finding the best algorithms and optimal configurations for their specific situation. This is accomplished by recording as much information on a certain model as the developer wants, and then analyzing all the data to find which algorithms work best on a dataset and with what settings to they work best.

Features

  • Record results from a machine learning algorithm test
  • Saves results in a Firebase Database
  • (Coming Soon) View results in a WebUI
  • (Coming Soon) Analyze data from results in the WebUI

Terminology

Test

Unless otherwise stated, when we say test we mean a way of determining if an algorithm works. (As opposed to testing of the actual code, etc..)

Result Record

All the information about the test including hyper-parameters of the model used, information on the test data, results of test, etc.

Getting Started

Prerequisites

Installation

While each sub-module can be installed separately, we have provided a simple install script that will install all the sub-modules globally.

./install.sh

While global install is preferred, if for some reason you don't want to install it globally (such as you do not have root privileges), the scripts can be run locally.

Setup

After installing MLTA, the first thing to run is:

mlta config

or if MLTA is not installed globally, navigate to '../mlta-config' and run

./mlta-config.js

Configuration is managed on a per person, per project basis and should be run for each project, for each user. Configuration files are stored in ~/.mlta/[PROJECT-NAME].config

Usage

To learn more about using MLTA, go to each sub-module you view their usage instructions.

Sub-Modules

This module is really just a collection of sub-modules that were designed to work together to accomplish the overarching goal of finding the optimal algorithm.

MLTA-Config

This module is for setting up your system with your project that uses MLTA. By having this handled separately from the other sub-modules, the user only has to handle authentication and other settings once as opposed to having to set it up for each sub-module individually.

MLTA-Record

This module is for taking in all the data the user wants to save from a specific test of an algorithm and uploads it to a Firebase database.

(Coming Soon) MLTA-Analyze

This module launches a Node.js web server for viewing and analyzing the data collected from the tests in a WebUI.