Traditional machine learning models are built to generalize. And while that works well in many cases, it’s also their Achilles’ heel—they often miss the sharp edges, the anomalies, the rare patterns that matter most. But transformers changed the game. ...
Fuzzy logic has long offered an elegant framework for reasoning under uncertainty – but designing good fuzzy systems has remained more of an art than a science. What if we could automate the design of fuzzy systems, make their internals differentiable, and even train them via gradient descent? ...
My journey to automatically generate fuzzy rules for a fuzzy engine led me to frequency-based algorithms like Apriori and FP-Growth. As I tried to understand how they work, I began to wonder if it would be possible to write a simple classifier based purely on support values. When all features in a dataset are one-hot encoded, it’s possible to calculate the support value of each feature for a given classification target. ...