
MIS447 Quiz2-Exploring Machine Learning Concepts

Quiz
•
Science
•
12th Grade
•
Easy
Güray ARIK
Used 1+ times
FREE Resource
16 questions
Show all answers
1.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is one-hot encoding and why is it used?
One-hot encoding is a method for generating random numbers.
One-hot encoding is used to reduce the size of numerical data.
One-hot encoding is a technique for image compression.
One-hot encoding is a method to convert categorical variables into a binary format for machine learning.
2.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the advantage of k-fold cross validation?
It guarantees a perfect model performance.
It provides a more reliable estimate of model performance by using multiple training and validation sets.
It eliminates the need for any validation data.
It reduces the computational cost of training the model.
3.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Why is stratified sampling often preferred over purely random sampling when creating a test set in machine learning?
It ensures that the test set is smaller than the training set.
It guarantees that the test set contains an equal number of instances from each class.
It ensures that the test set is representative of the overall population by maintaining the proportions of specific subgroups (strata).
It reduces the computational cost of training the model.
4.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
When reshaping a NumPy array using the reshape() function, what will happen if you try to reshape an array into an incompatible shape?
The array will be reshaped successfully.
An error will occur indicating an incompatible shape.
The original array will be modified to the new shape.
The area will automatically adjust to fit the new shape.
5.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What does following code snippet do?
Plots a line graph of total bills over different days.
Creates a box plot showing the distribution of total bills across different days.
Generates a histogram of total bills.
Displays a box plot of tips versus total bills.
6.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What are the main differences between supervised and unsupervised learning?
Unsupervised learning uses a smaller dataset than supervised learning.
Supervised learning is faster than unsupervised learning.
Supervised learning can only be used for classification tasks.
Supervised learning requires labeled data, while unsupervised learning does not.
7.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Explain the concept of support vector machines.
Support Vector Machines are unsupervised learning models that cluster data points without labels.
Support Vector Machines are supervised learning models that find the optimal hyperplane to separate different classes in high-dimensional space.
Support Vector Machines are primarily used for regression tasks in low-dimensional space.
Support Vector Machines rely on decision trees to classify data points.
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