Random occurrences in data mining results can be detected by dividing the data and building a model with one portion and using another portion to verify the results.

Question

Quizplus · Accepted Answer

This technique, often referred to as cross-validation, helps in detecting random occurrences or overfitting by validating the model on a separate set of data, ensuring that the patterns found are not just random noise but are generalizable to new data.

Random Occurrences in Data Mining Results Can Be Detected by Dividing