Exam AI-900 topic 1 question 27 discussion

Answer is Features

Features is right answer

1. features https://learn.microsoft.com/en-us/training/modules/create-regression-model-azure-machine-learning-designer/2-regression-scenarios Regression is a form of machine learning used to understand the relationships between variables to predict a desired outcome. Regression predicts a numeric label or outcome based on variables, or features. For example, an automobile sales company might use the characteristics of a car (such as engine size, number of seats, mileage, and so on) to predict its likely selling price. In this case, the characteristics of the car are the features, and the selling price is the label.

On exam Jul 26, 2024

correct

Input = Features

Answer is Features

Features is correct answer.

Features is correct answer.

Answer is features

I remember it as Data = Features i.e Words items, and Price or No = Lables - Answer is correcct

I remember it as Data = Features i.e Words items, and Price or No = Lables

Features

Feature selection and engineering directly impact the predicted labels. Answer should be Features.

features

features! a result is a label

Tricky one, all features must be dependant variables for the labeled data. So more correct answer will be A, as not all Features add value to prediction. That's why you have a module for Feature Selection...maybe I will choose A over B