4 Reasons Your Machine Learning Model is Wrong (and How to Fix It)

By Bilal Mahmood, Bolt. There are a number of machine learning models to choose from. We can use Linear Regression to predict a value, Logistic Regression to classify distinct outcomes, and Neural Networks to model non-linear behaviors. When we build these models, we always use a set of historical data to help our machine learning algorithms learn what is the relationship between a set of input features to a predicted output. But even if this model can accurately predict a value from historical data, how do we know it will work as well on new data? Or more plainly, how do we evaluate whether a machine learning model is actually “good”? In this post we’ll walk through some common scenarios where a seemingly good machine learning model may still be wrong. We’ll show how you…


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