VFDTVery Fast Decision Tree (algorithm)
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Pedro Domingos et al., 2000, proposed Very Fast Decision Tree (VFDT), which is one of the first algorithm that can learn from high speed data streams with small constant time per example and is based on Hoeffding Tree which uses Hoeffding Bound to choose best node splitting attribute.
Gama et al., 2006, proposed VFDT for continuous attributes (VFDTc) has the ability to deal with numerical data and provides more powerful classification for continuous data than VFDT.
One-class Very Fast Decision Tree algorithm OcVFDT is a single class classifier derived from VFDT. Its computational speed and accuracy is good when applied to the data stream that focuses on negative examples (Chen Li et al., 2009).