Machine learning
The data to which a ML algorithm is applied is called a training set, which consists of a set of pairs (x
, y
), called training examples. The pairs are explained as follows:
x
: This is a vector of values, often called the feature vector. Each value, or feature, can be categorical (values are taken from a set of discrete values, such as{S, M, L}
) or numerical.y
: This is the label, the classification or regression values forx
.
The objective of the ML process is to discover a function that best predicts the value of y
associated with each value of x
. The type of y
is in principle arbitrary, but there are several common and important ...
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