Machine Learning Explorer in Shiny
Shiny toolkit for data science modeling using machine learning
In affliation with the NYC Data Science Academy
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[...]
- 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.
You may need to import the shiny package prior to the runApp() call.
Alternatively you can display code in parallel to the app by using the following instead of the latter:
runApp("app",display.mode = "showcase")