Overcoming 'Big Data' Barriers in Machine Learning Techniques for the Real-Life Applications

摘要

Data analysis, regardless of whether the data are expected to explain a quantitative (as in regression) or categorical (as in classification) models, often requires overcoming various barriers. They include unbalanced datasets, faulty measurement results, and incomplete data.