The Data Scientist's Holy Grail -- Labeled Data Sets

The Holy Grail for data scientists is the ability to obtain labeled data sets for the purpose of training a supervised machine learning algorithm. An algorithm's ability to "learn" is based on training it using a labeled training set -- having known response variable values that correspond to a number of predictor variable values. There are a number of common and maybe not-so-common methods for labeling a data set. In this article, we'll run down a short list of such methods and then you can choose the best for your specific circumstances. Sometimes, labeled datasets are readily available as a byproduct of on-going business operations.