Other classification methods?

The perceptron is great, but not enough for all we need!

Uncertainty estimates?

The perceptron gives scores that only mean that one instance is more negative/positive than another. No notion of certainty/probability.

The sigmoid function $\sigma$ "squishes" any real number between 0 and 1:

Logistic regression: $P(y = 1) = \sigma(\mathbf{w} \cdot \mathbf{x})$

Multiclass classification?

Not all classifications we need are binary:

  • topic genres
  • fine-grained sentiment classification
  • essay scoring according to different aspects

The binary percepton cannot do it...

Many of them together though can!

One against all

  • Training: one binary classifier for each class against the rest
  • Testing: apply all classifiers, the highest scoring one wins

Non-linear classification

  • Linear classifiers (perceptron, logistic regression, etc.) can't solve this
  • Partly responsible for one AI winter
  • Neural networks with appropriate architecture can!


  • Learned how to represent text with numbers
  • How to learn binary linear classifiers with the perceptron
  • Got a taste of feature engineering
  • Saw some extensions for more advanced classification tasks