COMPUTER SCIENCE AND ENGINEERING
MACHINE LEARNING
|
Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
|
|
|
Supervised Learning
|
|
|
Unsupervised Learning
|
|
|
Either A or B
|
|
|
None of the above
|
Detailed explanation-1: -The testing data is used to get a measurement of how well the machine learning model predicts house prices. The machine learning model is given the test data but without the price of the properties in order to predict the price for them given the various features for the properties.
Detailed explanation-2: -Regression algorithms, on the other hand, predict the continuous value i.e. the expected price of a house; the number of votes that a party is likely to get in general elections, the number of marks a student is expected to score etc.
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.
Detailed explanation-4: -Machine Learning from Scratch series: Smart Discounts with Logistic Regression. Predicting House Prices with Linear Regression.