DBpedia – Linked Data Fragments

Matches in DBpedia 2015-10 for { <http://dbpedia.org/resource/Online_machine_learning> ?p ?o }

• Online_machine_learning abstract "Online machine learning is used in the case where the data becomes available in a sequential fashion, in order to determine a mapping from the dataset to the corresponding labels. The key difference between online learning and batch learning (or "offline" learning) techniques, is that in online learning the mapping is updated after the arrival of every new datapoint in a scalable fashion, whereas batch techniques are used when one has access to the entire training dataset at once. Online learning could be used in the case of a process occurring in time, for example the value of a stock given its history and other external factors, in which case the mapping updates as time goes on and we get more and more samples. Ideally in online learning, the memory needed to store the function remains constant even with added datapoints, since the solution computed at one step is updated when a new datapoint becomes available, after which that datapoint can then be discarded. For many formulations, for example nonlinear kernel methods, true online learning is not possible, though a form of hybrid online learning with recursive algorithms can be used. In this case, the space requirements are no longer guaranteed to be constant since it requires storing all previous datapoints, but the solution may take less time to compute with the addition of a new datapoint, as compared to batch learning techniques.As in all machine learning problems, the goal of the algorithm is to minimize some performance criteria using a loss function. For example, with stock market prediction the algorithm may attempt to minimize the mean squared error between the predicted and true value of a stock. Another popular performance criterion is to minimize the number of mistakes when dealing with classification problems. In addition to applications of a sequential nature, online learning algorithms are also relevant in applications with huge amounts of data such that traditional learning approaches that use the entire data set in aggregate are computationally infeasible.".
• Online_machine_learning wikiPageExternalLink ,.
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• Online_machine_learning wikiPageOutDegree "26".
• Online_machine_learning wikiPageRevisionID "680070507".
• Online_machine_learning wikiPageWikiLink Category:Machine_learning_algorithms.
• Online_machine_learning wikiPageWikiLink Empirical_risk_minimization.
• Online_machine_learning wikiPageWikiLink Hierarchical_temporal_memory.
• Online_machine_learning wikiPageWikiLink I.i.d..
• Online_machine_learning wikiPageWikiLink Independent_and_identically_distributed_random_variables.
• Online_machine_learning wikiPageWikiLink K-nearest_neighbor_algorithm.
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• Online_machine_learning wikiPageWikiLink Kernel_methods.
• Online_machine_learning wikiPageWikiLink Lazy_learning.
• Online_machine_learning wikiPageWikiLink Learning_Vector_Quantization.
• Online_machine_learning wikiPageWikiLink Learning_vector_quantization.
• Online_machine_learning wikiPageWikiLink Least_squares.
• Online_machine_learning wikiPageWikiLink Loss_function.
• Online_machine_learning wikiPageWikiLink Machine_learning.
• Online_machine_learning wikiPageWikiLink Mean_squared_error.
• Online_machine_learning wikiPageWikiLink Nicolò_Cesa-Bianchi.
• Online_machine_learning wikiPageWikiLink Offline_learning.
• Online_machine_learning wikiPageWikiLink Online_algorithm.
• Online_machine_learning wikiPageWikiLink Perceptron.
• Online_machine_learning wikiPageWikiLink Recursive_least_squares.
• Online_machine_learning wikiPageWikiLink Recursive_least_squares_filter.
• Online_machine_learning wikiPageWikiLink Stochastic_gradient_descent.
• Online_machine_learning wikiPageWikiLink Streaming_Algorithm.
• Online_machine_learning wikiPageWikiLink Streaming_algorithm.
• Online_machine_learning wikiPageWikiLink Supervised_learning.
• Online_machine_learning wikiPageWikiLink Support_vector_machine.
• Online_machine_learning wikiPageWikiLink Support_vector_machines.
• Online_machine_learning wikiPageWikiLink Tikhonov_regularization.
• Online_machine_learning wikiPageWikiLinkText "Learning Theory ".
• Online_machine_learning wikiPageWikiLinkText "Online learning".
• Online_machine_learning wikiPageWikiLinkText "Online machine learning".
• Online_machine_learning wikiPageWikiLinkText "adapt its model to previously unseen data".
• Online_machine_learning wikiPageWikiLinkText "on-line".
• Online_machine_learning wikiPageWikiLinkText "online algorithm".
• Online_machine_learning wikiPageWikiLinkText "online learning".
• Online_machine_learning wikiPageWikiLinkText "online machine learning".
• Online_machine_learning wikiPageWikiLinkText "online".
• Online_machine_learning hasPhotoCollection Online_machine_learning.
• Online_machine_learning wikiPageUsesTemplate Template:Machine_learning_bar.
• Online_machine_learning wikiPageUsesTemplate Template:Multiple_issues.
• Online_machine_learning subject Category:Machine_learning_algorithms.
• Online_machine_learning type Article.
• Online_machine_learning type Algorithm.
• Online_machine_learning type Article.
• Online_machine_learning type Thing.
• Online_machine_learning comment "Online machine learning is used in the case where the data becomes available in a sequential fashion, in order to determine a mapping from the dataset to the corresponding labels. The key difference between online learning and batch learning (or "offline" learning) techniques, is that in online learning the mapping is updated after the arrival of every new datapoint in a scalable fashion, whereas batch techniques are used when one has access to the entire training dataset at once.".
• Online_machine_learning label "Online machine learning".
• Online_machine_learning sameAs Algorithme_dapprentissage_incrxc3xa9mental.
• Online_machine_learning sameAs m.04q9r7w.
• Online_machine_learning sameAs Q7094097.
• Online_machine_learning sameAs Q7094097.
• Online_machine_learning wasDerivedFrom Online_machine_learning?oldid=680070507.
• Online_machine_learning isPrimaryTopicOf Online_machine_learning.