- k-nearest neighbors algorithm: An algorithm that estimates an unknown data item as being like the majority of the k-closest neighbors to that item.
- Naive Bayes classifier: A way to classify a data item using Bayes' theorem concerning the conditional probabilities P(A|B)=(P(B|A) * P(A))/P(B). It also assumes that variables in the data are independent, which means that no variable affects the probability of the remaining variables attaining a certain value.
- Decision tree: A model classifying a data item into one of the classes at the leaf node, based on matching properties between the branches on the tree and the actual data item.
- Random decision tree: A decision tree in which every branch is formed using only a random subset of the available variables during its construction.
- Random forest: An ensemble of random decision...
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