For each problem, please provide detail solution and written answers in a separate Excel tab. Your model must be stored in different tab to get full credit: The Royalty Gold Corporation prospects for undiscovered gold deposits around the world. The company is currently investigating a possible site on the island of Milos off the coast of Greece in the Mediterranean. When prospecting, the company drills to collect soil and rock samples and then analyzes the chemical properties of the samples to help determine whether or not the site is likely to contain significant gold deposits. Gold is made up of various elements including calavarite, sylvanite, and petzite. Sites with higher concentrations of these elements are more likely to contain significant gold deposits. The company has collected the data found in D2L representing the average levels of calavarite, sylvanite, and petzite in samples collected from previous various sites examined in previous prospecting expeditions. These data are grouped according to whether or not significant gold deposits were found at the location (1=significant, 2=insignificant).

Use a single classification tree to create a classifier for this data (with normalized inputs and at least 4 observations per terminal node). Create a graphic depiction of the best pruned tree using the validation data. How accurate is this procedure on the training data and validation data sets?

. G. Use a manual neural network to create a classifier for this data (use normalized inputs and a single hidden layer with 3 nodes). How accurate is this procedure on the training and validation data sets?