Find-S algorithm is a basic concept learning algorithm in machine learning. Find-S algorithm finds the most specific hypothesis that fits all the positive examples. We have to note here that the algorithm considers only those positive training example. Find-S algorithm starts with the most specific hypothesis and generalizes this hypothesis each time it fails to classify an observed positive training data. Hence, Find-S algorithm moves from the most specific hypothesis to the most general hypothesis. Important Representation :
? indicates that any value is acceptable for the attribute.
specify a single required value ( e.g., Cold ) for the attribute.
ϕindicates that no value is acceptable.
The most general hypothesis is represented by: {?, ?, ?, ?, ?, ?}
The most specific hypothesis is represented by : {ϕ, ϕ, ϕ, ϕ, ϕ, ϕ}