Step function
A step function is a piecewise-constant function that changes abruptly between discrete output values when its input crosses one or more specified thresholds.
Grokking Machine Learning
A threshold function that maps an input to one of discrete constant values according to whether the input crosses a specified threshold.
- How it is used
- Converts perceptron scores into binary class predictions.
- How deep it goes
- Defines the threshold rule, writes its formula, graphs its output, and implements it in Python before using it in a perceptron.
- Examples
- Uses alien moods, word-count features, separating lines, and Python prediction code as concrete examples.
- What you can do after
- Apply it via a Python prediction function to convert a perceptron score into a binary label.
Natural Language Processing in Action, Second Edition
A step function maps a value to one of discrete outputs according to whether it crosses a specified threshold.
- How it is used
- Converts a perceptron’s weighted input sum into a binary firing decision.
- How deep it goes
- Defines thresholding and demonstrates its Python expression, stopping short of training or backward propagation.
- Examples
- Uses a bag-of-words phrase, random weights, a -0.76 sum, and a zero-threshold Python expression.
- What you can do after
- Apply it via Python to turn a neuron’s numerical output into a binary prediction.
Read how Natural Language Processing in Action, Second Edition explains step function →
Related concepts
- activation functionkind of · An activation function maps a neural-network unit’s or layer’s input to an output, often introducing nonlinearity into the network’s computation.
- perceptronused by · A perceptron is a single-layer computational model and linear classifier that combines weighted inputs with a bias and applies a threshold or activation rule.
- generationused by · Generation is the computational production of outputs from supplied inputs or context, often by applying a model to produce predictions or new content.
- cumulative distribution functionused by · A cumulative distribution function gives the probability that a random variable is less than or equal to each specified value.
- sigmoidalternative to · A sigmoid is a smooth, bounded, S-shaped function that maps real-valued inputs between two limiting values, commonly zero and one.
- language modelused by · A language model is a computational model that represents patterns in linguistic tokens to estimate sequence probabilities and predict or generate language from context.
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