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  2. Reciprocal human machine learning - Wikipedia

    en.wikipedia.org/wiki/Reciprocal_human_machine...

    Reciprocal Human Machine Learning (RHML) is an interdisciplinary approach to designing human-AI interaction systems. [1] RHML aims to enable continual learning between humans and machine learning models by having them learn from each other. This approach keeps the human expert "in the loop" to oversee and enhance machine learning performance ...

  3. Knowledge graph embedding - Wikipedia

    en.wikipedia.org/wiki/Knowledge_graph_embedding

    The machine learning task for knowledge graph embedding that is more often used to evaluate the embedding accuracy of the models is the link prediction. [ 1 ] [ 3 ] [ 5 ] [ 6 ] [ 7 ] [ 18 ] Rossi et al. [ 5 ] produced an extensive benchmark of the models, but also other surveys produces similar results.

  4. Recurrent neural network - Wikipedia

    en.wikipedia.org/wiki/Recurrent_neural_network

    [7] [8] In 1933, Lorente de Nó discovered "recurrent, reciprocal connections" by Golgi's method, and proposed that excitatory loops explain certain aspects of the vestibulo-ocular reflex. [ 9 ] [ 10 ] During 1940s, multiple people proposed the existence of feedback in the brain, which was a contrast to the previous understanding of the neural ...

  5. Mean reciprocal rank - Wikipedia

    en.wikipedia.org/wiki/Mean_Reciprocal_Rank

    The mean reciprocal rank is a statistic measure for evaluating any process that produces a list of possible responses to a sample of queries, ordered by probability of correctness. The reciprocal rank of a query response is the multiplicative inverse of the rank of the first correct answer: 1 for first place, 1 ⁄ 2 for second place, 1 ⁄ 3 ...

  6. Learning to rank - Wikipedia

    en.wikipedia.org/wiki/Learning_to_rank

    Learning to rank [1] or machine-learned ranking (MLR) is the application of machine learning, typically supervised, semi-supervised or reinforcement learning, in the construction of ranking models for information retrieval systems. [2] Training data may, for example, consist of lists of items with some partial order specified between items in ...

  7. Harmonic mean - Wikipedia

    en.wikipedia.org/wiki/Harmonic_mean

    In computer science, specifically information retrieval and machine learning, the harmonic mean of the precision (true positives per predicted positive) and the recall (true positives per real positive) is often used as an aggregated performance score for the evaluation of algorithms and systems: the F-score (or F-measure).

  8. Category:Machine learning - Wikipedia

    en.wikipedia.org/wiki/Category:Machine_learning

    Machine learning is a branch of statistics and computer science which studies algorithms and architectures that learn from observed facts. The main article for this category is Machine learning . Wikimedia Commons has media related to Machine learning .

  9. Vowpal Wabbit - Wikipedia

    en.wikipedia.org/wiki/Vowpal_Wabbit

    Vowpal Wabbit's interactive learning support is particularly notable including Contextual Bandits, Active Learning, and forms of guided Reinforcement Learning. Vowpal Wabbit provides an efficient scalable out-of-core implementation with support for a number of machine learning reductions , importance weighting, and a selection of different loss ...

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