Python Machine Learning By Example - Second Edition

Best practice 2 – collecting all fields that are relevant

With a set goal in mind, we can narrow down potential data sources to investigate. Now the question becomes: is it necessary to collect the data of all fields available in a data source, or is a subset of attributes enough? It would be perfect if we knew in advance which attributes were key indicators or key predictive factors. However, it is in fact very difficult to ensure that the attributes hand-picked by a domain expert will yield the best prediction results. Hence, for each data source, it is recommended to collect all of the fields that are related to the project, especially in cases where recollecting the data is time consuming, or even impossible.

For example, in the stock ...