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Machine learningand data mining. 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.
e. Word2vec is a technique in natural language processing (NLP) for obtaining vector representations of words. These vectors capture information about the meaning of the word based on the surrounding words. The word2vec algorithm estimates these representations by modeling text in a large corpus. Once trained, such a model can detect synonymous ...
Machine learningand data mining. A self-organizing map (SOM) or self-organizing feature map (SOFM) is an unsupervised machine learning technique used to produce a low-dimensional (typically two-dimensional) representation of a higher-dimensional data set while preserving the topological structure of the data.
t. e. An autoencoder is a type of artificial neural network used to learn efficient codings of unlabeled data (unsupervised learning). [1][2] 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.
Multiple instance learning (MIL) falls under the supervised learning framework, where every training instance has a label, either discrete or real valued. MIL deals with problems with incomplete knowledge of labels in training sets. More precisely, in multiple-instance learning, the training set consists of labeled "bags", each of which is a ...
The wake-sleep algorithm[1] is an unsupervised learning algorithm for deep generative models, especially Helmholtz Machines. [2] The algorithm is similar to the expectation-maximization algorithm, [3] and optimizes the model likelihood for observed data. [4] The name of the algorithm derives from its use of two learning phases, the “wake ...
A step-wise schematic illustrating a generic Michigan-style learning classifier system learning cycle performing supervised learning. Keeping in mind that LCS is a paradigm for genetic-based machine learning rather than a specific method, the following outlines key elements of a generic, modern (i.e. post-XCS) LCS algorithm.
fastText is a library for learning of word embeddings and text classification created by Facebook's AI Research (FAIR) lab. [3] [4] [5] [6] The model allows one to ...