BADM 211. Quizzes (phase 1 + 3)
Which statement is true regarding prediction and classification problems?
- Predicting whether it would rain tomorrow is an example of classification problem
- Prediction is concerned with predicting a categorical outcome while classification is
concerned with grouping similar observations together.
- Predicting whether it would rain tomorrow is an example of prediction problem
- The same problem may be both prediction and classification at the same time. -
answerPredicting whether it would rain tomorrow is an example of classification problem
Outcome variables are relevant in the case of
- Classification
- Both prediction and classification
- Prediction
- Clustering - answerBoth prediction and classification
Classification and prediction are two types of unsupervised learning.
- True, in both the problems an outcome variable is specified.
- False, in both the problems an outcome variable is specified.
- True, neither has an outcome variable specified.
- False, neither has an outcome variable specified. - answerFalse, in both the problems
an outcome variable is specified.
Which of the following could be a likely cause of overfitting?
- Too many rows in the data
- Many predictors are correlated
- Almost none of the predictors are correlated to each other
, - Too many predictors - answerToo many predictors
Why would we partition our data into train and validation partitions?
- To fit separate models on each partition and compare models for their performance
- To fit different models on the two datasets and take average performance of the two
models
- Because the data could be too large to work with
- To test the model performance on data that has not been used to develop the model -
answerTo test the model performance on data that has not been used to develop the
model
In the term "K-fold cross validation," what does K refer to?
- K is the number of rows in the dataset
- K is number of predictors used
- K is the number of equal-sized groups into which the data are divided
- K is the size of each such group - answerK is the number of equal-sized groups into
which the data are divided
Which of the following is an example of supervised learning?
- A store manager, without any supervision from her manager, attempting to predict
sales for tomorrow.
- A newbie data scientist tasked with reducing the number of predictors based on the
correlation among them
- A seasoned data scientist attempting to develop a new algorithm to create
multidimensional charts.
- A store manager, under the supervision of her manager, attempting to group
customers into a few segments. - answerA store manager, without any supervision from
her manager, attempting to predict sales for tomorrow
Classification and prediction constitute:
- Predictive analytics
Which statement is true regarding prediction and classification problems?
- Predicting whether it would rain tomorrow is an example of classification problem
- Prediction is concerned with predicting a categorical outcome while classification is
concerned with grouping similar observations together.
- Predicting whether it would rain tomorrow is an example of prediction problem
- The same problem may be both prediction and classification at the same time. -
answerPredicting whether it would rain tomorrow is an example of classification problem
Outcome variables are relevant in the case of
- Classification
- Both prediction and classification
- Prediction
- Clustering - answerBoth prediction and classification
Classification and prediction are two types of unsupervised learning.
- True, in both the problems an outcome variable is specified.
- False, in both the problems an outcome variable is specified.
- True, neither has an outcome variable specified.
- False, neither has an outcome variable specified. - answerFalse, in both the problems
an outcome variable is specified.
Which of the following could be a likely cause of overfitting?
- Too many rows in the data
- Many predictors are correlated
- Almost none of the predictors are correlated to each other
, - Too many predictors - answerToo many predictors
Why would we partition our data into train and validation partitions?
- To fit separate models on each partition and compare models for their performance
- To fit different models on the two datasets and take average performance of the two
models
- Because the data could be too large to work with
- To test the model performance on data that has not been used to develop the model -
answerTo test the model performance on data that has not been used to develop the
model
In the term "K-fold cross validation," what does K refer to?
- K is the number of rows in the dataset
- K is number of predictors used
- K is the number of equal-sized groups into which the data are divided
- K is the size of each such group - answerK is the number of equal-sized groups into
which the data are divided
Which of the following is an example of supervised learning?
- A store manager, without any supervision from her manager, attempting to predict
sales for tomorrow.
- A newbie data scientist tasked with reducing the number of predictors based on the
correlation among them
- A seasoned data scientist attempting to develop a new algorithm to create
multidimensional charts.
- A store manager, under the supervision of her manager, attempting to group
customers into a few segments. - answerA store manager, without any supervision from
her manager, attempting to predict sales for tomorrow
Classification and prediction constitute:
- Predictive analytics
