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  2. Unsupervised learning - Wikipedia

    en.wikipedia.org/wiki/Unsupervised_learning

    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 .

  3. Active learning (machine learning) - Wikipedia

    en.wikipedia.org/wiki/Active_learning_(machine...

    Active learning is a special case of machine learning in which a learning algorithm can interactively query a human user (or some other information source), to label new data points with the desired outputs. The human user must possess knowledge/expertise in the problem domain, including the ability to consult/research authoritative sources ...

  4. Competitive learning - Wikipedia

    en.wikipedia.org/wiki/Competitive_learning

    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.

  5. Generalized Hebbian algorithm - Wikipedia

    en.wikipedia.org/wiki/Generalized_Hebbian_algorithm

    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 ...

  6. Autoencoder - Wikipedia

    en.wikipedia.org/wiki/Autoencoder

    An autoencoder is a type of artificial neural network used to learn efficient codings of unlabeled data (unsupervised learning).An autoencoder learns two functions: an encoding function that transforms the input data, and a decoding function that recreates the input data from the encoded representation.

  7. Category:Unsupervised learning - Wikipedia

    en.wikipedia.org/wiki/Category:Unsupervised_learning

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  8. Self-organizing map - Wikipedia

    en.wikipedia.org/wiki/Self-organizing_map

    The examples are usually administered several times as iterations. The training utilizes competitive learning. When a training example is fed to the network, its Euclidean distance to all weight vectors is computed. The neuron whose weight vector is most similar to the input is called the best matching unit (BMU). The weights of the BMU and ...

  9. Active transport - Wikipedia

    en.wikipedia.org/wiki/Active_transport

    There are two types of active transport: primary active transport that uses adenosine triphosphate (ATP), and secondary active transport that uses an electrochemical gradient. This process is in contrast to passive transport , which allows molecules or ions to move down their concentration gradient, from an area of high concentration to an area ...