Evaluation Metrics for Unsupervised Learning Algorithms

Alternatively, a similarity function might also be used. Machine learning techniques are usually classified into supervised and unsupervised techniques. Supervised machine learning starts from prior knowledge of the desired result 1) Scale Invariance: The first of Kleinberg's axioms states in the form of labeled data sets, which allows to guide the that f(d) f(α · d) for any distance function d and any training process, whereas unsupervised machine learning scaling factor α 0. [3] works directly on unlabeled data. In the absence of labels to orient the learning process, these labels must be "discovered" This simple axiom indicates that a clustering algorithm by the learning algorithm.