The most likely concern with a one-feature, machine-learning model is high error due to:
A statistician notices gaps in data associated with age-related illnesses and wants to further aggregate these observations. Which of the following is the best technique to achieve this goal?
Which of the following distributions would be best to use for hypothesis testing on a data set with 20 observations?
A data scientist wants to predict a person's travel destination. The options are:
Branson, Missouri, United States
Mount Kilimanjaro, Tanzania
Disneyland Paris, Paris, France
Sydney Opera House, Sydney, Australia
Which of the following models would best fit this use case?
Which of the following methods should a data scientist use just before switching to a potential replacement model?
The following graphic shows the results of an unsupervised, machine-learning clustering model:
k is the number of clusters, and n is the processing time required to run the model. Which of the following is the best value of k to optimize both accuracy and processing requirements?
Which of the following best describes the minimization of the residual term in a LASSO linear regression?
An analyst is examining data from an array of temperature sensors and sees that one sensor consistently returns values that are much higher than the values from the other sensors. Which of the following terms best describes this type of error?
Which of the following modeling tools is appropriate for solving a scheduling problem?
Which of the following describes the appropriate use case for PCA?