文件名称:active_learning-master

  • 所属分类:
  • matlab例程
  • 资源属性:
  • [Matlab] [源码]
  • 上传时间:
  • 2015-01-31
  • 文件大小:
  • 48kb
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  • 0次
  • 提 供 者:
  • w*
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active learning

This software package provides a toolbox for testing pool-based active-learning algorithms in MATLAB.-This software package provides a toolbox for testing pool-based active-learning algorithms in MATLAB.
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下载文件列表





active_learning-master

......................\LICENSE

......................\README.md

......................\active_learning.m

......................\label_oracles

......................\.............\bernoulli_oracle.m

......................\.............\label_oracles.m

......................\.............\lookup_oracle.m

......................\.............\multinomial_oracle.m

......................\models

......................\......\cheating_model.m

......................\......\ensemble.m

......................\......\gaussian_process_model.m

......................\......\knn_model.m

......................\......\label_propagation_model.m

......................\......\model_memory_wrapper.m

......................\......\models.m

......................\......\random_forest_model.m

......................\other

......................\.....\get_label_oracle.m

......................\.....\get_model.m

......................\.....\get_query_strategy.m

......................\.....\get_score_function.m

......................\.....\get_selector.m

......................\query_strategies

......................\................\argmax.m

......................\................\argmin.m

......................\................\expected_error_reduction.m

......................\................\margin_sampling.m

......................\................\query_by_committee.m

......................\................\query_strategies.m

......................\................\uncertainty_sampling.m

......................\score_functions

......................\...............\calculate_entropies.m

......................\...............\expected_loss_lookahead.m

......................\...............\expected_loss_naive.m

......................\...............\expected_utility_lookahead.m

......................\...............\expected_utility_naive.m

......................\...............\loss_functions

......................\...............\..............\expected_01_loss.m

......................\...............\..............\expected_log_loss.m

......................\...............\..............\loss_functions.m

......................\...............\margin.m

......................\...............\marginal_entropy.m

......................\...............\score_functions.m

......................\selectors

......................\.........\fixed_test_set_selector.m

......................\.........\graph_walk_selector.m

......................\.........\identity_selector.m

......................\.........\meta_selectors

......................\.........\..............\complement_selector.m

......................\.........\..............\intersection_selector.m

......................\.........\..............\union_selector.m

......................\.........\probability_treshold_selector.m

......................\.........\random_selector.m

......................\.........\selectors.m

......................\.........\unlabeled_selector.m

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