Common Machine Learning Obstacles - KDnuggets

Engineers and scientists who are modeling with machine learning often face challenges when working with data. Two of the most common obstacles relate to choosing the right classification model and eliminating data overfitting. Classification models assign items to a discrete group or class based on a specific set of features.Determining the best classification model often presents difficulties given the uniqueness of each dataset and desired outcome. Overfitting occurs when the model is too closely aligned with limited training data that may contain noise or errors. An overfit model is not able to generalize well to data outside the training set, limiting its usefulness in a production system.