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bnclassify  

Learning Discrete Bayesian Network Classifiers from Data
View on CRAN: Click here


Download and install bnclassify package within the R console
Install from CRAN:
install.packages("bnclassify")

Install from Github:
library("remotes")
install_github("cran/bnclassify")

Install by package version:
library("remotes")
install_version("bnclassify", "0.4.8")



Attach the package and use:
library("bnclassify")
Maintained by
Mihaljevic Bojan
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2015-07-30
Latest Update: 2022-11-16
Description:
State-of-the art algorithms for learning discrete Bayesian network classifiers from data, including a number of those described in Bielza & Larranaga (2014) , with functions for prediction, model evaluation and inspection.
How to cite:
Mihaljevic Bojan (2015). bnclassify: Learning Discrete Bayesian Network Classifiers from Data. R package version 0.4.8, https://cran.r-project.org/web/packages/bnclassify. Accessed 22 Dec. 2024.
Previous versions and publish date:
0.3.0 (2015-07-30 11:27), 0.3.1 (2015-10-29 15:19), 0.3.2 (2015-11-19 11:02), 0.3.3 (2017-09-06 19:29), 0.3.4 (2018-01-13 01:32), 0.4.0 (2018-05-08 15:51), 0.4.1 (2018-07-25 11:50), 0.4.2 (2019-03-14 14:33), 0.4.3 (2019-11-30 02:20), 0.4.4 (2020-01-20 20:20), 0.4.5 (2020-03-12 18:40), 0.4.6 (2021-10-30 01:10), 0.4.7 (2022-11-16 13:11)
Other packages that cited bnclassify R package
View bnclassify citation profile
Other R packages that bnclassify depends, imports, suggests or enhances
Complete documentation for bnclassify
Functions, R codes and Examples using the bnclassify R package
Some associated functions: accuracy . aode . are_factors . are_pdists . as_mlr . augment_kdb . augment_kdb_arcs . augment_ode . augment_ode_arcs . bnc . bnc_aode . bnc_aode_bns . bnc_bn . bnc_dag . bnclassify . bootstrap_ss . car . check_mlr_attached . cmi . cmi_table . complete_graph . compute_cll . compute_ll . compute_wanbia_weights . cpt_vars_values . cv . dag . direct_forest . direct_tree . extract_ctgt . fast_equal . forget . get_ancestors . get_but_last . get_last . get_log_leaf_entries . get_null_safe . grain_and_graph . graph_add_edges . graph_connected_components . graph_get_adjacent . graph_is_adjacent . graph_named_edge_matrix . graph_subgraph . graph_union . greedy_wrapper . identify_all_testing_depths . identify_min_testing_depths . inspect_bnc_bn . inspect_bnc_dag . is.memoised . is_aode . learn_params . learn_unprunned_tree . local_ode_score_contrib . log_normalize . loglik . makeRLearner.bnc . make_cll . make_cll_gradient . map . max_weight_forest . memoise_char . named_edge_matrix . nb . nb_dag . new_cache . order_acyclic . plot.bnc_dag . predict.bnc_fit . predictLearner.bnc . print.bnc_base . skip_assert . skip_testing . spode . subset_by_colnames . superparent_children . tan_chowliu . trainLearner.bnc . voting . 
Some associated R codes: 0bnclassify-doc.R . RcppExports.R . anb-bn-operate.R . anb-bn.R . anb-cpts.R . anb-dag.R . anb-families.R . anb-internal.R . basic-assert.R . basic-misc.R . basic-probs.R . bnc-dag-operate.R . bncs.R . cv-update.R . cv.R . data-input.R . data-statistics.R . frontend-dag.R . infer.R . learn-chowliu.R . learn-hc-operators.R . learn-hc.R . learn-params-awnb.R . learn-params-manb.R . learn-params-wanbia.R . learn-params.R . learn-struct.R . memoise.R . predict.R . release.R . wrap-gRain.R . wrap-graph.R . wrap-mlr.R . wrap-rpart.R .  Full bnclassify package functions and examples
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