Which of the following is a supervised learning problem? (multiple options may be correct)
Predicting credit approval based on historical data
Grouping people in a social network.
Predicting the gender of a person from his/her image. You are given the data of 1 Million images along the gender.
Given the class labels of old news articles, predicting the class of a new news article from its content. Class of a news article can be such as sports, politics, technology, etc.
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Supervised learning are predicting credit approval based on historical data,
predicting the gender of person from his/her images.
Explanation:
- Supervised learning is example of predicting the dependent variable.
- There can be n number of independent variable but one dependent.
- If the data is too large use Naive Bayes else use Linear SVM & Naive.
- Explainable Decision three and logistics regression.
- Speed and Accuracy Kernel SVM,Random Forest, Neural network.
- It has gradient boosting tree.
- Linear regression uses the algorithms OLS ( Ordinary least square)
TO Learn more:-
- https://brainly.in/question/15275511
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