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Machine learningand data mining. Self-supervised learning (SSL) is a paradigm in machine learning where a model is trained on a task using the data itself to generate supervisory signals, rather than relying on external labels provided by humans. In the context of neural networks, self-supervised learning aims to leverage inherent structures or ...
BERT (language model) Bidirectional encoder representations from transformers (BERT) is a language model introduced in October 2018 by researchers at Google. [ 1 ][ 2 ] It learns to represent text as a sequence of vectors using self-supervised learning. It uses the encoder-only transformer architecture.
e. Decision tree learning is a supervised learning approach used in statistics, data mining and machine learning. In this formalism, a classification or regression decision tree is used as a predictive model to draw conclusions about a set of observations. Tree models where the target variable can take a discrete set of values are called ...
Weak supervision is a paradigm in machine learning, the relevance and notability of which increased with the advent of large language models due to large amount of data required to train them. It is characterized by using a combination of a small amount of human- labeled data (exclusively used in more expensive and time-consuming supervised ...
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 ...
A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier. [9] [10]For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model. [11]
Ensemble learning trains two or more Machine Learning algorithms to a specific classification or regression task. The algorithms within the ensemble learning model are generally referred as "base models", "base learners" or "weak learners" in literature. The base models can be constructed using a single modelling algorithm or several different ...
Category. : Flora of Gabon. Wikimedia Commons has media related to Flora of Gabon. This category contains the native flora of Gabon as defined by the World Geographical Scheme for Recording Plant Distributions. Taxa of the lowest rank are always included; taxa of higher ranks (e.g. genus) are only included if monotypic or endemic.