Exam AI-900 topic 1 question 33 discussion

this is wrong. the answer should be C- classification as the the prediction whether the loan will be repaid or not -- whether means class - categorical asnwer as yes or no - hence clasification

Correct answer is "A" I am a data Scientist & 100% sure

classification = labeling regression = continous values i think the confusion comes with Logistic regression (true/false values) Despite its name, it does NOT predict continuous values like linear regression. It predicts probabilities and converts them into categories (e.g., "Yes" or "No").

classification : yes or no

I'm not a doctor, but I play one on TV. And it's classification.

Whether -> Classification

Correct answer is "C" I am a Banker on Wall Street & 100% sure

1. classification https://learn.microsoft.com/en-us/training/modules/create-classification-model-azure-machine-learning-designer/classification-scenarios Classification is a form of machine learning that is used to predict which category, or class, an item belongs to. This machine learning technique can be applied to binary and multi-class scenarios. For example, a health clinic might use the characteristics of a patient (such as age, weight, blood pressure, and so on) to predict whether the patient is at risk of diabetes. In this case, the characteristics of the patient are the features, and the label is a binary classification of either 0 or 1, representing non-diabetic or diabetic.

The correct answer is Classification and now has been corrected in the Exam Topic's too.

A banking system that predicts whether a loan will be repaid is not an example of the regression type of machine learning. Regression is a technique for predicting continuous outcomes based on the relationship between features and a target variable ⁴. In the case of predicting whether a loan will be repaid or not, the outcome is binary (repaid or not repaid) and not continuous. Therefore, classification would be a more appropriate type of machine learning for this task. Source: Conversation with Bing, 4/24/2023 (1) Machine Learning Regression Explained - Seldon. https://www.seldon.io/machine-learning-regression-explained Accessed 4/24/2023. (2) . https://bing.com/search?q=regression+machine+learning Accessed 4/24/2023. (3) Regression in Machine Learning: What It Is & Examples | Built In. https://builtin.com/data-science/regression-machine-learning Accessed 4/24/2023. (4) Machine Learning: Regression | Coursera. https://www.coursera.org/learn/ml-regression Accessed 4/24/2023.

Appeared in exam, 04/04/2023

We are predicting a discrete/categorical target variable. So answer must be classification

why not regressino, it's a yes or no question?

Answer is Classification;

Classification is correct answer.

on test 14/6/22

A is correct