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86. The selling price of a house depends on the following factors. For example, it depends on the number of bedrooms, number of kitchen, number of bathrooms, the year the house was built and the square footage of the lot. Given these factors predicting the selling price of the house is an example of __________ task.
Binary Classification
Multilabel Classification
Simple Linear Regression
Multiple Linear Regression
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87. A student grade is a variable F1 which can take values from: A, B, C, D, E & F. Which of the following statements is true in the following case?
Variable F1 is an example of nominal variable.
Variable F1 is an example of ordinal variable.
It doesn't belong to any of the above category.
None of the above
88. Regarding bias and variance, which of the following statements are true?(Here 'high' and 'low' are relative to the ideal mode.) a. Models which overfit are more likely to have high bias b. Models which overfit are more likely to have low bias c. Models which overfit are more likely to have high variance d. Models which overfit are more likely to have low variance
a and c
a and d
b and c
b and d
89. During the treatment of cancer patients, the doctor needs to be very careful about which patients need to be given chemotherapy. Which metric should we use in order to decide the patients who should be given chemotherapy? a. Precision b. Recall
a only
b only
Both a and b
90. Imagine a newly-born starts to learn walking. It will try to find a suitable policy to learn walking after repeated falling and getting up. Specify what type of machine learning algorithm is best suited to do the same.
Supervised Learning
Unsupervised Learning
Reinforcement Learning
Semi-supervised Learning
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