Dataset : Iris.csv It is assumed that a dataset that has a class attribute (used for a…

Dataset : Iris.csv

It is assumed that a dataset that has a class attribute (used for a classification problem) has 10 classes
that are recorded as numeric values: 0, 1, 2, .. 9. However, these numeric values are assigned to the
classes arbitrarily. There is no ordinal ranking meaning among them. It is similar to the case of the
values 0 and 1 that are used to represent NO (or NEGATIVE) and YES (or POSITIVE).
The dataset will be used in a deep learning project.
Question 1.1:
Using critical thinking and based on the lectures, is it necessary to perform any kind of coding (integer
coding or one-hot coding) on these class values for better performance of the project?
Question 1.2:
If the answer to Question 1.1 is “YES,” what type(s) of encoding needs to be done to process the class
values before using the dataset for the deep learning project?
Question 1.3:
Based on the answer to Question 1.2, explain the steps of what needs to be done for each type of
encoding.
Question 1.4:
Based on the answer to Question 1.2, perform the necessary encoding tasks to transform the class values
before using the dataset for the deep learning project.
–) We need to provide the answers/solutions to each of the above questions.
–) Display the results of the encoding task.

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