sider the Boston Housing Data file (The schema of the data filing

a. Study the Neural Networks Prediction example from the URL:

http://www.solver.com/xlminer/help/neural-networks-classification-intro, and following the example

step by step (using the manual neural network classification example)

b. Using XLMINER’s neural network routine under predict menu to fit a model using XLMINER default

values for neural network parameters by using the predictors such as CRIM, ZN, INDUS, CHAS, NOX,

RM, AGE, DIS, RAD, TAX, PTRATIO, B, LSTAT to predict the value of the outcome variable

MEDV.

i. Record the RMS errors for the training data and the validation data, and observe the lift charts

for repeating the process, changing the number of epochs to 300, 3000, 10,000, 20,000.

ii. What happens to RMS error for the training data set as the number of epochs increases?

iii. What happens to RMS error for the validation data set as the number of epochs increases?

iv. Comments on the appropriate number of epochs for the model.

Note: (Please use the Prediction Option of the Neural Network in order to get RMS error)

c. Please submit your execution results and answers included in MS Excel file

Note:

1. The file BostonHousing.xls is posted along Written Assignment #3B, and description of columns are

given in the file.

2. The cloud based XLMiner is accessible by the URL: https://www.analyticsolver.com

3. For the Windows based XLMiner, please check the XLMiner download instruction posted in