Question
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
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-bearing ore is made up of various minerals including calaverite, sylvanite, and petzite. Sites with higher concentrations of these minerals are more likely to contain significant gold deposits. The company has collected the data found in the file RoyalGold.xlsm accompanying this book representing the average levels of calaverite, 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).
a. What are the coordinates of the centroids for the significant sites and the insignificant sites? Round your answers to three decimal places, if necessary.
Centroids | ||||||
Group | Calavarite | Sylvanite | Petzite | |||
1 | ||||||
2 |
b. Use XLMiner's standard data partition command to partition the data into a training set (with 60% of the observations) and validation set (with 40% of the observations) using the default seed of 12345. Use discriminant analysis to create a classifier for this data. How accurate is this procedure on the training and validation data sets? Round your answers to one decimal place.
Data Set | Overall Error | |
Training | % | |
Validation | % |
c. Use logistic regression to create a classifier for this data. How accurate is this procedure on the training and validation data sets? Round your answers to one decimal place.
Data Set | Overall Error | |
Training | % | |
Validation | % |
d. Use the k-nearest neighbor technique to create a classifier for this data (with normalized inputs). What value of k seems to work best?
How accurate is this procedure on the training and validation data sets? Round your answers to one decimal place.
Data Set | Overall Error | |
Training | % | |
Validation | % |
e. 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 and validation data sets? Round your answers to one decimal place.
Data Set | Overall Error | |
Training | % | |
Validation | % |
f. Use a manual neural network to create a classifier for this data (rescale the data using standardization, use a single hidden layer with 3 neurons, use a stopping rule on training only with 300 epochs and a maximum of 50 epochs without improvement). How accurate is this procedure on the training and validation data sets? Round your answers to one decimal place.
Data Set | Overall Error | |
Training | % | |
Validation | % |
g. Return to the Data sheet and use the Transform, Bin Continuous Data command to create binned variables for Calaverite, Sylvanite, and Petzite. Use XLMiner's standard data partition command to partition the data into a training set (with 60% of the observations) and validation set (with 40% of the observations) using the default seed of 12345. Now use the nave Bayes technique to create a classifier for the data using the new binned variables for Calaverite, Sylvanite, and Petzite. How accurate is this procedure on the training and validation data sets? Round your answers to one decimal place.
Data Set | Overall Error | |
Training | % | |
Validation | % |
h. Which of the classification techniques would you recommend the company actually use? SelectDiscriminant analysisLogistic regressionk-nearest neighbor (k = 3)k-nearest neighbor (k optimized)Classification treeNeural networkNaive BayesItem 20
i. Suppose the company analyzes five sites on Milos that produce the following average levels of calaverite, sylvanite, and petzite. According to your recommended classifier, which of these sites, if any, should be considered for further analysis?
Site | Gold deposit |
1 | |
2 | |
3 | |
4 | |
5 |
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