Learning Discrete Bayesian Network Classifiers from Data

Vignettes

- README.md
- methods
- overview
- `bnclassify`: Learning Bayesian Network Classifiers
- Methods' details for the `bnclassify` package

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**accuracy:**Compute predictive accuracy.**aode:**Learn an AODE ensemble.**are_factors:**Checks if all columns in a data frame are factors.**are_pdists:**Returns 'TRUE' is 'x' is a valid probability distribution.**as_mlr:**Convert to 'mlr'.**augment_kdb:**Arcs that do not invalidate the k-DB structure**augment_kdb_arcs:**Returns augmenting arcs that do not invalidate the k-DB.**augment_ode:**Arcs that do not invalidate the tree-like structure**augment_ode_arcs:**Returns augmenting arcs that do not invalidate the ODE.**bnc:**Learn network structure and parameters.**bnc_aode:**Returns a 'c("bnc_aode", "bnc")' object.**bnc_aode_bns:**Fits an AODE model.**bnc_bn:**Bayesian network classifier with structure and parameters.**bnc_dag:**Bayesian network classifier structure.**bnclassify:**Learn discrete Bayesian network classifiers from data.**bootstrap_ss:**Return a bootstrap sub-sample.**car:**Car Evaluation Data Set.**check_mlr_attached:**Checks if mlr attached.**cmi:**Compute the (conditional) mutual information between two...**cmi_table:**Returns the conditional mutual information three variables.**complete_graph:**Returns a complete unweighted graph with the given nodes.**compute_cll:**Computes the conditional log-likelihood of the model on the...**compute_ll:**Computes log-likelihood of the model on the provided data.**compute_wanbia_weights:**Compute WANBIA weights. Computes feature weights by...**cpt_vars_values:**Get just form first dimension in their own cpt, not checking...**cv:**Estimate predictive accuracy with stratified cross...**dag:**Get underlying graph. This should be exported.**direct_forest:**Direct an undirected graph.**direct_tree:**Direct an undirected graph.**extract_ctgt:**Returns a contingency table over the variables.**fast_equal:**Compares all elements in a to b**forget:**Forget a memoized function.**get_ancestors:**Based on gRbase::ancestors()**get_but_last:**Return all but last element of x.**get_last:**Return last element of x.**get_log_leaf_entries:**Assuming that the cpt is a leaf, returns 1 instead of a CPT...**get_null_safe:**Get i-th element of x.**grain_and_graph:**Convert to graph and gRain.**graph_add_edges:**Add edges Does not allow edges among adjacent nodes**graph_connected_components:**connected_components**graph_get_adjacent:**Finds adjacent nodes. Has not been tested much**graph_is_adjacent:**Checks whether nodes are adjacent**graph_named_edge_matrix:**Returns an edge matrix with node names (instead of node...**graph_subgraph:**Subgraph. Only for a directed graph?**graph_union:**Merges multiple disjoint graphs into a single one.**greedy_wrapper:**Learn Bayesian network classifiers in a a greedy wrapper...**identify_all_testing_depths:**Identifies all depths at which the features of a...**identify_min_testing_depths:**Identifies the lowest (closest to root) depths at which the...**inspect_bnc_bn:**Inspect a Bayesian network classifier (with structure and...**inspect_bnc_dag:**Inspect a Bayesian network classifier structure.**Browse all...**

Returns a naive Bayes structure

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