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BUSI 651 – Machine Learning

Assignment 2:

The provided dataset “Franchises Dataset” contains data collected from different 100 franchises.

The data contains the net profit (million $) for each franchise, the counter sales (million $), the

drive-through sales (million $), and the type of the franchise.

Address the following questions:

a) Develop a Neural Network (NN) prediction model for the net profit (Number of layers =

3, dense layers, activation function of Tan, number of nodes in each layer = 20).

b) What is the forecast of the net profit, if the counter sales are 500,000 $, drive-through

sales are 700,000$, and the franchise is a pizza store. Comment on the forecasted value.

c) What are the limitations of the model?

Submit a PDF file for your answers as well as the excel sheet. Include the Python code in the
PDF.

Due to June 8, 2022.

Franchise_data

Net Profit Counter Sales Drive-through Sales Business Type

2 8.4 7.7 1 Café 1

1.3 3.3 4.5 1 Pizza Store 2

1.2 5.8 8.4 2 Burger store 3

2.4 10 7.8 3

0.7 4.7 2.4 1

1.3 7.7 4.8 1

1.1 4.5 2.5 1

2.3 8.6 3.4 3

0.9 5.9 2 1

1.6 6.3 4.1 3

2 8.4 7.7 1

1.3 3.3 4.5 1

1.7 5.8 8.4 1

1.4 10 7.8 2

1.2 4.7 2.4 3

1.8 7.7 4.8 3

1.6 4.5 2.5 3

1.8 8.6 3.4 1

1.4 5.9 2 3

1.1 6.3 4.1 1

1.5 8.4 7.7 2

1.3 3.3 4.5 1

1.2 5.8 8.4 2

2.4 10 7.8 3

1.2 4.7 2.4 3

1.3 7.7 4.8 1

1.1 4.5 2.5 1

1.3 8.6 3.4 2

0.9 5.9 2 1

1.6 6.3 4.1 3

2 8.4 7.7 1

0.8 3.3 4.5 2

2.2 5.8 8.4 3

2.4 10 7.8 3

1.2 4.7 2.4 3

0.8 7.7 4.8 2

1.6 4.5 2.5 3

1.8 8.6 3.4 1

0.9 5.9 2 1

1.6 6.3 4.1 3

2 8.4 7.7 1

0.8 3.3 4.5 2

1.2 5.8 8.4 2

1.9 10 7.8 1

0.7 4.7 2.4 1

0.8 7.7 4.8 2

0.6 4.5 2.5 2

2.3 8.6 3.4 3

0.9 5.9 2 1

1.6 6.3 4.1 3

2 8.4 7.7 1

1.3 3.3 4.5 1

1.2 5.8 8.4 2

2.4 10 7.8 3

0.7 4.7 2.4 1

1.8 7.7 4.8 3

0.6 4.5 2.5 2

2.3 8.6 3.4 3

0.4 5.9 2 2

1.1 6.3 4.1 1

2.5 8.4 7.7 3

1.8 3.3 4.5 3

2.2 5.8 8.4 3

2.4 10 7.8 3

1.2 4.7 2.4 3

0.8 7.7 4.8 2

1.1 4.5 2.5 1

1.3 8.6 3.4 2

0.9 5.9 2 1

0.6 6.3 4.1 2

2.5 8.4 7.7 3

1.3 3.3 4.5 1

2.2 5.8 8.4 3

1.9 10 7.8 1

0.2 4.7 2.4 2

1.8 7.7 4.8 3

1.6 4.5 2.5 3

2.3 8.6 3.4 3

1.4 5.9 2 3

0.6 6.3 4.1 2

1.7 8.4 7.7 2

1.8 3.3 4.5 3

2.6 5.8 8.4 3

1.4 10 7.8 2

0.2 4.7 2.4 2

1 7.7 4.8 2

0.6 4.5 2.5 2

2.3 8.6 3.4 3

1.6 5.9 2 1

0.6 6.3 4.1 2

2.5 8.4 7.7 3

1.6 3.3 4.5 3

1.2 5.8 8.3 2

1.9 9.8 7.8 1

1.2 4.7 2.4 3

1.8 7.7 4.8 3

0.6 4.5 2.5 2

1.3 9.1 3.4 2

1 5.9 2.2 1

1.8 6.3 4.2 3