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Unsupervised learning is a framework in machine learning where, in contrast to supervised learning, algorithms learn patterns exclusively from unlabeled data. [1] Other frameworks in the spectrum of supervisions include weak- or semi-supervision , where a small portion of the data is tagged, and self-supervision .
Three types of plate boundary Convergent boundary Divergent boundary Transform boundary. Tectonic plate interactions are classified into three basic types: [1] Convergent boundaries are areas where plates move toward each other and collide. These are also known as compressional or destructive boundaries.
Earthquakes are common along convergent boundaries. A region of high earthquake activity, the Wadati–Benioff zone, generally dips 45° and marks the subducting plate. Earthquakes will occur to a depth of 670 km (416 mi) along the Wadati-Benioff margin. [citation needed] Both compressional and extensional forces act along convergent boundaries.
Island arcs are long chains of active volcanoes with intense seismic activity found along convergent tectonic plate boundaries. Most island arcs originate on oceanic crust and have resulted from the descent of the lithosphere into the mantle along the subduction zone. They are the principal way by which continental growth is achieved. [1]
Continental-continental divergent/constructive boundary Oceanic divergent boundary: mid-ocean ridge (cross-section/cut-away view). In plate tectonics, a divergent boundary or divergent plate boundary (also known as a constructive boundary or an extensional boundary) is a linear feature that exists between two tectonic plates that are moving away from each other.
The generalized Hebbian algorithm is an iterative algorithm to find the highest principal component vectors, in an algorithmic form that resembles unsupervised Hebbian learning in neural networks. Consider a one-layered neural network with n {\displaystyle n} input neurons and m {\displaystyle m} output neurons y 1 , … , y m {\displaystyle y ...
Competitive learning is a form of unsupervised learning in artificial neural networks, in which nodes compete for the right to respond to a subset of the input data. [ 1 ] [ 2 ] A variant of Hebbian learning , competitive learning works by increasing the specialization of each node in the network.
Obduction is a geological process whereby denser oceanic crust (and even upper mantle) is scraped off a descending ocean plate at a convergent plate boundary and thrust on top of an adjacent plate. [1] [2] When oceanic and continental plates converge, normally the denser oceanic crust sinks under the continental crust in the process of ...