You are hired as a data analyst for Diamonds Inc., a company who appraises diamonds. The company…

You are hired as a data analyst for Diamonds Inc., a company who appraises diamonds. The company
would like to automate appraisals for future shipments and you are responsible for developing the
method of automatization. A sample of the training and testing data is given. For reference, you are given a dataset containing 48547 diamonds with the
following characteristics (variables):

price price in US dollars ($326–$18,823)
carat weight of the diamond (0.2–5.01)
cut quality of the cut (Fair, Good, Very Good, Premium, Ideal)
color diamond color, from J (worst) to D (best)
clarity a measurement of how clear the diamond is (I1 (worst), SI2, SI1, VS2, VS1, VVS2, VVS1, IF (best))
x length in mm (0–10.74)
y width in mm (0–58.9)
z depth in mm (0–31.8)
depth total depth percentage = z / mean(x, y) = 2 * z / (x + y) (43–79)
table width of top of diamond relative to widest point (43–95)
Your task is:
1.) Create the machine learning model to appraise the price of diamonds based on their

a. Use the unsupervised data mining method Association Rules to create automatization.

b. in python, use the training dataset to train your model.. (please show code since i am only providing a sample of the code)

c. Use your model to make predictions on the testing dataset. Evaluate the precision of your
model using the metrics.
d. Save script.

2.) Reporting the details.

– Goal of your work (e.g.: automatic appraisal system)
– Short description of the methods used (e.g.: Regression Tree, what it does, how you
used it)
– Data collection (you just need to describe the training dataset to show the CEO what
you worked with)
– Results (show how precise you model is by evaluating your using your chosen
metrics for the testing dataset).

testing set:

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