What ratio of number_of_training_instances vs. number_of_training_features is a good thumb rule for getting a good fit machine learning model?
Say we have 10 features and 10 training instances, i.e. ratio is one. We will not get a good fit model.
What ratio can I use as a thumb rule to validate datasets before training?