Some simple ways to measure machine learning models

Today’s post is a short one, but focuses on two types of machine learning models that are commonly used in GTM use cases: classification and clustering.

For classification models, you’re trying to measure the accuracy of your predictions, so you’ll see that most of the measure are related to how many positive outcomes were found, etc.

For clustering models, you’re trying to find clusters that are really tightly knit, but are far away from other clusters, so you’ll see that these measures incorporate things like variance and distance between data points or clusters.

That’s it from me today!