If I have 100 people fill out a multiple choice questionnaire (containing 10 questions with 5 answer choices for each question) and the respondent writes their gender on their questionnaire, what is the best way to guess the gender of a new person that submits the questionnaire but does not write their gender?
This would be a classification problem. You can use binary classifier labeling male and female. I'm assuming the question number would be the feature and the answers the observations. There are many classification algorithms however you should perform some kind of exploratory analysis before you attempt to classify to get a better understanding of the required preprocessing, feature importance, scaling etc. This would direct you towards the algorithm that you may want to use. Try sklearn which has many prepossessing tools and some easy to use classification algorithms.
- This would be a classification problem as @IDontKnowCode has mentioned
- If the questions remain the same for everybody, you can have 10(questions) * 5(answer choice) = 50 features
- Fit a decision tree or any other classification problem into this data set
This should be a quick excercise. Best of luck :)
As mentioned by others, problem mentioned is most probably a classification based problem.
Also Data Pre-processing will play an important role here. For e.g. a particular feature (say Education) may have certain ordering among values (High-school, Bachelors, Masters).
You should make sure that such cases are well handled before selecting/building a Machine Learning Model.