To examine the local housing market in a particular region, a sample of 120 homes sold during a year are collected. The data are given below:

Partition the data into training (50 percent), validation (30 percent), and test (20 percent) sets. Predict the sale price using a regression tree. Use Sale Price as the output variable and all the other variables as input variables. In Step 2 of XLMiner's Regression Tree procedure, be sure to Normalize input data, to set the Maximum #splits for input variables to 59, to set the Minimum #records in a terminal node to 1, and specify Using Best prune tree as the scoring option. In Step 3 of XLMiner's Regression Tree procedure, set the maximum number of levels to 7. Generate the Full tree and Best pruned tree.
a. In terms of number of decision nodes, compare the size of the full tree to the size of the best pruned tree.
b. What is the root mean squared error (RMSE) of the best pruned tree on the validation data and on the test data?
c. What is the average error on the validation data and test data? What does this suggest?
d. By examining the best pruned tree, what are the critical variables in predicting the sale price of a home?

Question

To examine the local housing market in a particular region, a sample of 120 homes sold during a year are collected. The data are given below:

Partition the data into training (50 percent), validation (30 percent), and test (20 percent) sets. Predict the sale price using a regression tree. Use Sale Price as the output variable and all the other variables as input variables. In Step 2 of XLMiner's Regression Tree procedure, be sure to Normalize input data, to set the Maximum #splits for input variables to 59, to set the Minimum #records in a terminal node to 1, and specify Using Best prune tree as the scoring option. In Step 3 of XLMiner's Regression Tree procedure, set the maximum number of levels to 7. Generate the Full tree and Best pruned tree. 
a. In terms of number of decision nodes, compare the size of the full tree to the size of the best pruned tree.
b. What is the root mean squared error (RMSE) of the best pruned tree on the validation data and on the test data?
c. What is the average error on the validation data and test data? What does this suggest?
d. By examining the best pruned tree, what are the critical variables in predicting the sale price of a home?

Quizplus · Accepted Answer

The Answer of To examine the local housing market in a particular region, a sample of 120 homes sold during a year are collected. The data are given below:

Partition the data into training (50 percent), validation (30 percent), and test (20 percent) sets. Predict the sale price using a regression tree. Use Sale Price as the output variable and all the other variables as input variables. In Step 2 of XLMiner's Regression Tree procedure, be sure to Normalize input data, to set the Maximum #splits for input variables to 59, to set the Minimum #records in a terminal node to 1, and specify Using Best prune tree as the scoring option. In Step 3 of XLMiner's Regression Tree procedure, set the maximum number of levels to 7. Generate the Full tree and Best pruned tree. 
a. In terms of number of decision nodes, compare the size of the full tree to the size of the best pruned tree.
b. What is the root mean squared error (RMSE) of the best pruned tree on the validation data and on the test data?
c. What is the average error on the validation data and test data? What does this suggest?
d. By examining the best pruned tree, what are the critical variables in predicting the sale price of a home?

To Examine the Local Housing Market in a Particular Region