Which of the following can be considered as unsupervised learning $($clustering$)$ problems? Select all that apply.

Which of the following can be considered as unsupervised learning $($clustering$)$ problems? Select all that apply.

Based on past data of children living in low$-$income families, a model is implemented to predict physical, mental, and educational outcomes of children as a function of their family income.

A popular web browser collects a set of online news articles and uses its algorithm to group them into different categories based on their topic, key texts, location, and relevance. It uses its user$$s browsing history to personalise news feed so that different users can see different categories of news

A credit card company is feeding a large amount of data on historical credit card transactions conducted by its customers to a learning model to detect fraudulent transactions.

Utilising the daily trading data of S&P $500$ for the last $60$ days, you are trying to predict whether the market will open below its $5-$day moving average tomorrow.

A bank is feeding thousands of daily transactions into a model to detect unusual behaviour in transactions that has not been detected before. The model is expected to distinguish patterns between genuine day$-$to$-$day transactions and unusual fraudulent transactions.