APPLICATION OF SUPERVISED LEARNING
NEURAL NETWORK
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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Predict the price of a house
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Supervised Learning
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Unsupervised Learning
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Either A or B
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None of the above
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Explanation:
Detailed explanation-1: -The Random Forest was found to consistently perform better than the k-NN algorithm in terms of smaller errors and be better suited as a prediction model for the house price problem.
Detailed explanation-2: -Machine Learning: Regression-predict house price (lesson 2)
Detailed explanation-3: -House price prediction can help the developer determine the selling price of a house and can help the customer to arrange the right time to purchase a house. There are three factors that influence the price of a house which include physical conditions, concept and location.
There is 1 question to complete.