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ML Pythonprogramming~5 mins

Why regression predicts continuous values in ML Python - Quick Recap

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beginner
What type of values does regression predict?
Regression predicts continuous values, meaning it estimates numbers that can take any value within a range, like height or temperature.
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beginner
Why is regression used instead of classification for predicting continuous values?
Because regression models output a range of values, not fixed categories, making them suitable for tasks like predicting prices or temperatures.
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beginner
How does regression handle the output compared to classification?
Regression outputs a number on a continuous scale, while classification outputs a label from a set of categories.
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beginner
Give an example of a problem where regression is the right choice.
Predicting the price of a house based on its size and location is a regression problem because price is a continuous value.
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beginner
What does 'continuous value' mean in the context of regression?
It means the predicted value can be any number within a range, not just fixed options or categories.
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What kind of output does a regression model produce?
AA category label
BA true or false value
CA continuous number
DA list of categories
Which problem is best solved by regression?
AClassifying emails as spam or not spam
BPredicting temperature tomorrow
CIdentifying the species of a flower
DSorting images into folders
Why can regression predict values like 3.5 or 7.8?
ABecause it predicts fixed labels
BBecause it predicts categories
CBecause it predicts true/false
DBecause it predicts continuous values
Which of these is NOT a continuous value?
ANumber of cars in a parking lot
BWeight in kilograms
CTemperature in Celsius
DHeight in centimeters
What makes regression different from classification?
ARegression predicts numbers, classification predicts categories
BRegression predicts categories, classification predicts numbers
CRegression predicts true/false, classification predicts numbers
DRegression predicts text, classification predicts images
Explain why regression models predict continuous values instead of categories.
Describe a real-life example where regression is the best choice and why.