3. An analytics consultant at an insurance company has built an ABT that will be used to...

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3. An analytics consultant at an insurance company has built an ABT that will be used to train a model to predict the best communications channel to use to contact a potential customer with an offer of a new insurance product.15 The following table contains an extract from this ABT—the full ABT contains 5,200 instances.

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The descriptive features in this dataset are defined as follows:
AGE: The customer’s age GENDER: The customer’s gender (male or female)
LOC: The customer’s location (rural or urban)
OCC: The customer’s occupation MOTORINS: Whether the customer holds a motor insurance policy with the company (yes or no)
MOTORVALUE: The value of the car on the motor policy HEALTHINS: Whether the customer holds a health insurance policy with the company (yes or no)
HEALTHTYPE: The type of the health insurance policy (PlanA, PlanB, or PlanC)

saving).

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Discuss this data quality report in terms of the following:

a. Missing values

b. Irregular cardinality

c. Outliers

d. Feature distributions

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