What is not supervised learning?

Fall 23 Review

Quiz
•
Computers
•
12th Grade
•
Hard
ACM UCLA
Used 5+ times
FREE Resource
8 questions
Show all answers
1.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Training a model with labeled data -- giving it the expected answers!
Grouping people into friend groups based on data about their favorite movies!
Predicting the price of a house given historical data about cost of houses with known square footage.
Classifying cats and dogs, given pictures of each with labels.
2.
MULTIPLE SELECT QUESTION
45 sec • 1 pt
Which of the following is true? [2 correct]
Classification problems have a continuous output line
Classification predicts classes or categories
An example of regression is seeing if a picture is a cat or dog
Regression involves predicting the continuous relationship between input features and the output.
3.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What kind of training data should you provide a supervised learning model for best results?
Give the model one specific type of example data only.
Give the model a lot of diverse data.
Give the model unlabeled data
Give the model one or two examples only.
4.
MULTIPLE SELECT QUESTION
45 sec • 1 pt
What is linear regression?
The process of shifting weights and biases to minimize loss
Moving to the left along a line to optimize the learning rate.
Approximating a continuous (linear) output; finding the relationship between X and y
"Finding the line of best fit"
5.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is loss?
A number indicating how bad the model’s prediction was on a single example.
A function that transforms any number into a probability
A line that shows the relationship between input features and output
A line that separates classes
6.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Why is gradient descent important?
We want to make our predictions smaller, so descending helps
We use it to change the weights / biases to make our model more accurate
Gradient descent increases loss. More loss helps our model get close to 0
We use it to prevent the model from overfitting the data.
7.
MULTIPLE SELECT QUESTION
45 sec • 1 pt
What is mean squared error? 2 correct answers!
The absolute difference between actual value and predicted value
A loss function
The gradient of a function
8.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What do we call the line that separates two classes in logistic regression?
Decision boundary
Loss function
Line of best fit
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