Machine Learning Explorer in Shiny

Shiny toolkit for data science modeling using machine learning

Collaborators

Avi Yashchin
Jospeh Lee

Introduction

This shiny application is an exploratory toolkit using R. The purpose fo this project was to learn, exercise, and implement R code as well as an interactive front end using Shiny.

How to Run

There are two ways to run the program.

Run on Server

Go to the following link[...]

Run Locally

• Clone this repo to your local machine
• Download the following list of R packages or make sure you have recent versions if you already have them.

require(shiny);
require(shinyIncubator);
library(shinydashboard);
require(pastecs);
require(shiny);
require(caret);
require(e1071);
require(randomForest);
require(nnet);
require(glmnet);
require(gbm);
library(mice);
library(VIM);
require(fastICA);
library(googleVis);
library("PASWR");
require("doMC")
source("helpers.R")

• Open the terminal and 'cd' to the MLExplorerShiny folder and activate R console.
• If R studio was used then change the studio directory to appropriate folder using setwd().
  Once you are at the correct directory run the following R command.

runApp("app") 

You may need to import the shiny package prior to the runApp() call.

library(shiny)

Alternatively you can display code in parallel to the app by using the following instead of the latter:

runApp("app",display.mode = "showcase")