Diamond price prediction

In this presentation you can find the information regarding the Diamond price prediction application. The application can be found on the following link staj tvoj link

This application builds a linear regression model using the diamonds dataset and is predicting the price of the diamond depending of its properties, such as:

• Carat
• Cut
• Color
• Clarity

Then it builds a plot and gives the predicted price of the diamond.

The data used for this application is the diamonds dataset, which is part of the ggplot2 package. This dataset contains the information of arround 53940 diamonds with 10 different variables:

     carat               cut        color        clarity          depth      
 Min.   :0.2000   Fair     : 1610   D: 6775   SI1    :13065   Min.   :43.00  
 1st Qu.:0.4000   Good     : 4906   E: 9797   VS2    :12258   1st Qu.:61.00  
 Median :0.7000   Very Good:12082   F: 9542   SI2    : 9194   Median :61.80  
 Mean   :0.7979   Premium  :13791   G:11292   VS1    : 8171   Mean   :61.75  
 3rd Qu.:1.0400   Ideal    :21551   H: 8304   VVS2   : 5066   3rd Qu.:62.50  
 Max.   :5.0100                     I: 5422   VVS1   : 3655   Max.   :79.00  
                                    J: 2808   (Other): 2531                  
     table           price             x                y         
 Min.   :43.00   Min.   :  326   Min.   : 0.000   Min.   : 0.000  
 1st Qu.:56.00   1st Qu.:  950   1st Qu.: 4.710   1st Qu.: 4.720  
 Median :57.00   Median : 2401   Median : 5.700   Median : 5.710  
 Mean   :57.46   Mean   : 3933   Mean   : 5.731   Mean   : 5.735  
 3rd Qu.:59.00   3rd Qu.: 5324   3rd Qu.: 6.540   3rd Qu.: 6.540  
 Max.   :95.00   Max.   :18823   Max.   :10.740   Max.   :58.900  

       z         
 Min.   : 0.000  
 1st Qu.: 2.910  
 Median : 3.530  
 Mean   : 3.539  
 3rd Qu.: 4.040  
 Max.   :31.800  

The application is build using the Shiny package and the source code of the application is written in 2 files:

• ui.R
• server.R

The files can be found on the following link

The application is drawing plot of diamonds in the diamonds dataset distributed by their size (carat) and price ($). The regression line is shown on the plot as well in blue color.

By selecting specific features of the diamond (carat, cut, clarity, color) the user is able to sub select the dataset and the regression line is recalculated based only on the diamonds filtered in the dataset that share the same features. If no features are selected the regression model is using all diamonds in the data set.