QMB3302 Final Exam, QMB3302 Final UF
UPDATED Study Guide QUESTIONS
AND CORRECT ANSWERS
- Pipelines are useful (in analytics with Python sense) for the
following reasons? (choose all that apply)
- Pipelines make it easy to repeat/replicate steps and run multiple
models
- Pipelines are good for moving data into your programming
environment
- Pipelines automatically update to new versions of Python
- Pipelines help organize code you used to clean and treat your data
- Pipelines make it very easy to change small things in your model,
like which variable to include - CORRECT ANSWERS -
Pipelines make it easy to repeat/replicate steps and run multiple
models
- Pipelines help organize code you used to clean and treat your data
- Pipelines make it very easy to change small things in your model,
like which variable to include
The basic idea of a regression is very simple. We have some X value
(which we call ______) and some Y value that we are trying to _____.
We could have multiple Y value, but that is not something we have
covered. - CORRECT ANSWERS features; predict
Y and y-hat are a little different. Y is our target vector, and y-hat is an
output in our model that is a.... (choose one of the following)
- estimate or prediction of y
,- the actual value of y
- an axis on our 2 way graph
- a combination of XY intercept coordinates - CORRECT ANSWERS
estimate or prediction of y
When looking at the code in the videos, we sometimes used a variable
to hold out model. What is the significance of the word "model" in the
below code?
model = LinearRegression(fit_intercept=True) - CORRECT
ANSWERS 'model' is a named variable and is just holding our
linear regression model. It could be renamed anything. The word itself
is not important. It is just a container.
What is a good model fit value? - CORRECT ANSWERS
unknowable without knowing/understanding the context of the
domain
Imagine X in the below is a missing value. If I were to run a median
imputer on this set of data, what would the return value be?
50, 60, 70, 80, 100, 60, 5000, X - CORRECT ANSWERS 70
Which of the below were discussed as being problems with the
holdout method for validation?
- Data is not available for test and control differences
- Outliers can skew the result
,- The model is not trained on all of the data
- K=3 is not sufficiently large enough
- Validation is sometimes too challenging - CORRECT ANSWERS
- Outliers can skew the result
- The model is not trained on all of the data
The features in a model...
- are used as proxies for y-hat divided by y
- are always functions of each other
- keep the model validation process stable
- none of these answers are correct - CORRECT ANSWERS
none of these answers are correct
What is the first variable in a decision tree called (before any of the
branches)? - CORRECT ANSWERS root
One problem with decision trees is that they are prone to _____ if you
are not careful or do not set the _____ appropriately. - CORRECT
ANSWERS overfitting; max depth
True or False: The random forest algorithm prevents, or at least
avoids to some extent, the problems with overfitting found in decision
trees. - CORRECT ANSWERS True
True or False: Random Forests can only be used on classification
problems - CORRECT ANSWERS False
, True or False: In order to interpret Decision Tree's, it is necessary to
first run a linear regression - CORRECT ANSWERS False
True or False: Decision Tree's are nice because they are fairly simple
and straightforward to interpret - CORRECT ANSWERS True
When running our first decision tree, we took out "maxdepth=". This
had the unfortunate result of... - CORRECT ANSWERS
Building a very large hard to understand tree
What is the terminal node as discussed in the lecture? - CORRECT
ANSWERS The last node (sometimes called a leaf is you
google the term); the tree doesn't split after this
Models, such as the random forest model we ran, often have a number
of parameters that the analyst can choose or set.
What is a the best source of up to date information about the different
parameters that can be set? - CORRECT ANSWERS The scikit
learn documentation
Random forests are _____ interpretable than decision trees. -
CORRECT ANSWERS less
True or False: The correct number of clusters in Hierarchical
clustering can be determined precisely using approaches such as
silhouette scores. - CORRECT ANSWERS False
UPDATED Study Guide QUESTIONS
AND CORRECT ANSWERS
- Pipelines are useful (in analytics with Python sense) for the
following reasons? (choose all that apply)
- Pipelines make it easy to repeat/replicate steps and run multiple
models
- Pipelines are good for moving data into your programming
environment
- Pipelines automatically update to new versions of Python
- Pipelines help organize code you used to clean and treat your data
- Pipelines make it very easy to change small things in your model,
like which variable to include - CORRECT ANSWERS -
Pipelines make it easy to repeat/replicate steps and run multiple
models
- Pipelines help organize code you used to clean and treat your data
- Pipelines make it very easy to change small things in your model,
like which variable to include
The basic idea of a regression is very simple. We have some X value
(which we call ______) and some Y value that we are trying to _____.
We could have multiple Y value, but that is not something we have
covered. - CORRECT ANSWERS features; predict
Y and y-hat are a little different. Y is our target vector, and y-hat is an
output in our model that is a.... (choose one of the following)
- estimate or prediction of y
,- the actual value of y
- an axis on our 2 way graph
- a combination of XY intercept coordinates - CORRECT ANSWERS
estimate or prediction of y
When looking at the code in the videos, we sometimes used a variable
to hold out model. What is the significance of the word "model" in the
below code?
model = LinearRegression(fit_intercept=True) - CORRECT
ANSWERS 'model' is a named variable and is just holding our
linear regression model. It could be renamed anything. The word itself
is not important. It is just a container.
What is a good model fit value? - CORRECT ANSWERS
unknowable without knowing/understanding the context of the
domain
Imagine X in the below is a missing value. If I were to run a median
imputer on this set of data, what would the return value be?
50, 60, 70, 80, 100, 60, 5000, X - CORRECT ANSWERS 70
Which of the below were discussed as being problems with the
holdout method for validation?
- Data is not available for test and control differences
- Outliers can skew the result
,- The model is not trained on all of the data
- K=3 is not sufficiently large enough
- Validation is sometimes too challenging - CORRECT ANSWERS
- Outliers can skew the result
- The model is not trained on all of the data
The features in a model...
- are used as proxies for y-hat divided by y
- are always functions of each other
- keep the model validation process stable
- none of these answers are correct - CORRECT ANSWERS
none of these answers are correct
What is the first variable in a decision tree called (before any of the
branches)? - CORRECT ANSWERS root
One problem with decision trees is that they are prone to _____ if you
are not careful or do not set the _____ appropriately. - CORRECT
ANSWERS overfitting; max depth
True or False: The random forest algorithm prevents, or at least
avoids to some extent, the problems with overfitting found in decision
trees. - CORRECT ANSWERS True
True or False: Random Forests can only be used on classification
problems - CORRECT ANSWERS False
, True or False: In order to interpret Decision Tree's, it is necessary to
first run a linear regression - CORRECT ANSWERS False
True or False: Decision Tree's are nice because they are fairly simple
and straightforward to interpret - CORRECT ANSWERS True
When running our first decision tree, we took out "maxdepth=". This
had the unfortunate result of... - CORRECT ANSWERS
Building a very large hard to understand tree
What is the terminal node as discussed in the lecture? - CORRECT
ANSWERS The last node (sometimes called a leaf is you
google the term); the tree doesn't split after this
Models, such as the random forest model we ran, often have a number
of parameters that the analyst can choose or set.
What is a the best source of up to date information about the different
parameters that can be set? - CORRECT ANSWERS The scikit
learn documentation
Random forests are _____ interpretable than decision trees. -
CORRECT ANSWERS less
True or False: The correct number of clusters in Hierarchical
clustering can be determined precisely using approaches such as
silhouette scores. - CORRECT ANSWERS False
