QMB3302 UF FINAL EXAM
QUESTIONS WITH CORRECT
ANSWERS
The correct number of clusters in Hierarchical clustering can be
determined precisely using approaches such as silhouette scores (True
or False) -- Answer ✔✔ False
In K Means clustering, the analyst does not need to determine the
number of clusters (K), these are always derived analytically using the
kmeans algorithm. (True or False) -- Answer ✔✔ False
One big difference between the unsupervised approaches in this
module, and the supervised approaches in prior modules:
Unsupervised models do not have a target variable (Y). This make is
difficult to know when they are "right" or correct. (True or False) --
Answer ✔✔ True
According to the documentation, a silhouette scores of 1 ia -- Answer
✔✔ The best score
According to the documentation, a silhouette score of -1 is -- Answer
✔✔ The worst score
, Select all that apply. Imagine you have a data set with columns/inputs
for customers:
Column 1 = Customer ID (a number)
Column 2 = Sales (a dollar value)
Column 3= Frequency (a number)
Column 4 = Satisfaction (a number)
You would like to understand the impact of Frequency on customer
Satisfaction. What types of approaches could you use?
Note that the type of data is brackets () after the column name. --
Answer ✔✔ Decision tree, random forest, linear regression
Select all that apply. Imagine you have a dataset with the following
columns (inputs) for a set of customers.
Column 1 = Customer ID
Column 2 = Distance to Store
QUESTIONS WITH CORRECT
ANSWERS
The correct number of clusters in Hierarchical clustering can be
determined precisely using approaches such as silhouette scores (True
or False) -- Answer ✔✔ False
In K Means clustering, the analyst does not need to determine the
number of clusters (K), these are always derived analytically using the
kmeans algorithm. (True or False) -- Answer ✔✔ False
One big difference between the unsupervised approaches in this
module, and the supervised approaches in prior modules:
Unsupervised models do not have a target variable (Y). This make is
difficult to know when they are "right" or correct. (True or False) --
Answer ✔✔ True
According to the documentation, a silhouette scores of 1 ia -- Answer
✔✔ The best score
According to the documentation, a silhouette score of -1 is -- Answer
✔✔ The worst score
, Select all that apply. Imagine you have a data set with columns/inputs
for customers:
Column 1 = Customer ID (a number)
Column 2 = Sales (a dollar value)
Column 3= Frequency (a number)
Column 4 = Satisfaction (a number)
You would like to understand the impact of Frequency on customer
Satisfaction. What types of approaches could you use?
Note that the type of data is brackets () after the column name. --
Answer ✔✔ Decision tree, random forest, linear regression
Select all that apply. Imagine you have a dataset with the following
columns (inputs) for a set of customers.
Column 1 = Customer ID
Column 2 = Distance to Store
