Developing Data Products, Course Project

The following presentation is an introduction to a Shiny application that allows the user to see the impact of certain variables on the Median Value of Boston Homes. The program calculates the Median Values of Homes using 5 common regressions.

Additionally, the Root Mean Squared Error is calculated once initially for each regression type. Lower RMSE values are more accurate.

The application is available on

• https://bdietz77.shinyapps.io/DDP-Project

Note, that is may take a few seconds to load so please be patient! :)

This application is based on data originally published by Harrison, D. and Rubinfeld, D.L. 'Hedonic prices and the demand for clean air', J. Environ. Economics & Management, vol.5, 81-102, 1978.

The Original Dataset has been obtained from UCI Machine Learning Repository Dataset and processed as a part of peer assignment for the Coursera Course Developing Data Products.

The Dataset is described in the following url UCI MLR Archive

Source code is available on the GitHub.

Linear_model <- lm(MEDV~CRIM+ZN+INDUS+CHAS+
NOX+RM+AGE+DIS+RAD+TAX+PTRATIO+LSTAT,
data=housing)

RLM_model <- rlm(same as above)

EARTH_model <- earth(same as above)

MVR_model <- mvr(same as above)

SVM_model <- svm(same as above)

Call:
svm(formula = MEDV ~ CRIM + ZN + INDUS + CHAS + NOX + RM + AGE + 
    DIS + RAD + TAX + PTRATIO + LSTAT, data = housing)


Parameters:
   SVM-Type:  eps-regression 
 SVM-Kernel:  radial 
       cost:  1 
      gamma:  0.08333333 
    epsilon:  0.1 


Number of Support Vectors:  338