unsupervised search - определение. Что такое unsupervised search
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Что (кто) такое unsupervised search - определение

MACHINE LEARNING TECHNIQUE
Unsupervised approach; Unsupervised classification; Unsupervised machine learning; Self-taught AI; Self-taught artificial intelligence; Algorithms for unsupervised learning
  • Restricted Boltzmann Machine.  This is a Boltzmann machine where lateral connections within a layer are prohibited to make analysis tractable.
  •  This network has multiple RBM's to encode a hierarchy of hidden features.  After a single RBM is trained, another blue hidden layer (see left RBM) is added, and the top 2 layers are trained as a red & blue RBM.  Thus the middle layers of an RBM acts as hidden or visible, depending on the training phase it's in.
  • Tendency for a task to employ supervised vs. unsupervised methods. Task names straddling circle boundaries is intentional. It shows that the classical division of imaginative tasks (left) employing unsupervised methods is blurred in today's learning schemes.

Unsupervised learning         
Unsupervised learning is a type of algorithm that learns patterns from untagged data. The hope is that through mimicry, which is an important mode of learning in people, the machine is forced to build a compact internal representation of its world and then generate imaginative content from it.
Search analytics         
User:CrizCraig/Search Analytics; Search Analytics; Search engine history; Search engine analytics
Search analytics is the use of search data to investigate particular interactions among Web searchers, the search engine, or the content during searching episodes.Jansen, B.
Ternary search         
TECHNIQUE IN COMPUTER SCIENCE FOR FINDING THE MINIMUM OR MAXIMUM OF A UNIMODAL FUNCTION
Trinary search; Ternary Search
A ternary search algorithm is a technique in computer science for finding the minimum or maximum of a unimodal function. A ternary search determines either that the minimum or maximum cannot be in the first third of the domain or that it cannot be in the last third of the domain, then repeats on the remaining two thirds.

Википедия

Unsupervised learning

Unsupervised learning is a type of algorithm that learns patterns from untagged data. The goal is that through mimicry, which is an important mode of learning in people, the machine is forced to build a concise representation of its world and then generate imaginative content from it.

In contrast to supervised learning where data is tagged by an expert, e.g. tagged as a "ball" or "fish", unsupervised methods exhibit self-organization that captures patterns as probability densities or a combination of neural feature preferences encoded in the machine's weights and activations. The other levels in the supervision spectrum are reinforcement learning where the machine is given only a numerical performance score as guidance, and semi-supervised learning where a small portion of the data is tagged.