In this assignment you will test Multi Layer Perceptrons with different attributes to find the best suitable configuration for the data provided

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In this assignment you will test Multi Layer Perceptrons with different attributes to find the best suitable configuration for the data provided.

You will use Weka Data Mining Tool (http://www.cs.waikato.ac.nz/ml/weka/) to analyse these variations.

The data is available at Coadsys CSE462 course page.

• csv file contains the data.

• txt contains what are these values in the data file.

• arff is the format file that you must prepare for the provided data.

The data is for housing price prediction. It contains several attributes to define a house, its price and a purchase decision column. You have 500 rows of data. Use 400 for training and 100 for testing. You will be trying to recommend the purchase decision based on all the attributes given.

 

What you need to do for this assignment is the following tasks:

 

• Prepare the arff file with the data and the format

• Try 5 different combinations of the following attributes. Use a scientific approach (Keep all values constant and change only single value for each )

  • Number of epochs (training time)

  • Learning rate

  • Number of hidden layers

  • Momentum

• Take the screenshot of the best run for each

• Write a report to show graphics, screenshots and explanations about your tests on the house purchase decision data.

Attachments:

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