R package citation, R package reverse dependencies, R package scholars, install an r package from GitHub hy is package acceptance pending why is package undeliverable amazon why is package on hold dhl tour packages why in r package r and r package full form why is r free why r is bad which r package to install which r package has which r package which r package version which r package readxl which r package ggplot which r package fread which r package license where is package.json where is package-lock.json where is package.swift where is package explorer in eclipse where is package where is package manager unity where is package installer android where is package manager console in visual studio who r package which r package to install which r package version who is package who is package deal who is package design r and r package full form r and r package meaning what r package has what package r what is package in java what is package what is package-lock.json what is package in python what is package.json what is package installer do r package can't install r packages r can't find package r can't load package can't load xlsx package r can't install psych package r can't install sf package r Write if else in NONMEM pk pd
iai
View on CRAN: Click
here
Download and install iai package within the R console
Install from CRAN:
install.packages("iai")
Install from Github:
library("remotes")
install_github("cran/iai")
Install by package version:
library("remotes")
install_version("iai", "1.10.0")
Attach the package and use:
library("iai")
Maintained by
Jack Dunn
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2019-07-18
Latest Update: 2023-06-13
Description:
An interface to the algorithms of 'Interpretable AI'
from the R programming language.
'Interpretable AI' provides various modules, including 'Optimal Trees' for
classification, regression, prescription and survival analysis, 'Optimal
Imputation' for missing data imputation and outlier detection, and 'Optimal
Feature Selection' for exact sparse regression. The 'iai' package is an
open-source project. The 'Interpretable AI' software modules are proprietary
products, but free academic and evaluation licenses are available.
How to cite:
Jack Dunn (2019). iai: Interface to 'Interpretable AI' Modules. R package version 1.10.0, https://cran.r-project.org/web/packages/iai
Previous versions and publish date:
Other packages that cited iai R package
View iai citation profile
Other R packages that iai depends,
imports, suggests or enhances
Functions, R codes and Examples using
the iai R package
Some associated functions: acquire_license . add_julia_processes . all_treatment_combinations . apply . apply_nodes . as.mixeddata . autoplot.grid_search . autoplot.roc_curve . autoplot.similarity_comparison . autoplot.stability_analysis . categorical_classification_reward_estimator . categorical_regression_reward_estimator . categorical_reward_estimator . categorical_survival_reward_estimator . cleanup_installation . clone . convert_treatments_to_numeric . copy_splits_and_refit_leaves . decision_path . delete_rich_output_param . equal_propensity_estimator . fit.grid_search . fit.imputation_learner . fit.learner . fit . fit.optimal_feature_selection_learner . fit_and_expand . fit_cv . fit_predict.categorical_reward_estimator . fit_predict.numeric_reward_estimator . fit_predict . fit_transform . fit_transform_cv . get_best_params . get_classification_label.classification_tree_learner . get_classification_label.classification_tree_multi_learner . get_classification_label . get_classification_proba.classification_tree_learner . get_classification_proba.classification_tree_multi_learner . get_classification_proba . get_cluster_assignments . get_cluster_details . get_cluster_distances . get_depth . get_estimation_densities . get_features_used . get_grid_result_details . get_grid_result_summary . get_grid_results . get_learner . get_lower_child . get_machine_id . get_num_fits.glmnetcv_learner . get_num_fits . get_num_fits.optimal_feature_selection_learner . get_num_nodes . get_num_samples . get_params . get_parent . get_policy_treatment_outcome . get_policy_treatment_outcome_standard_error . get_policy_treatment_rank . get_prediction_constant.glmnetcv_learner . get_prediction_constant . get_prediction_constant.optimal_feature_selection_learner . get_prediction_weights.glmnetcv_learner . get_prediction_weights . get_prediction_weights.optimal_feature_selection_learner . get_prescription_treatment_rank . get_regression_constant.classification_tree_learner . get_regression_constant.classification_tree_multi_learner . get_regression_constant . get_regression_constant.prescription_tree_learner . get_regression_constant.regression_tree_learner . get_regression_constant.regression_tree_multi_learner . get_regression_constant.survival_tree_learner . get_regression_weights.classification_tree_learner . get_regression_weights.classification_tree_multi_learner . get_regression_weights . get_regression_weights.prescription_tree_learner . get_regression_weights.regression_tree_learner . get_regression_weights.regression_tree_multi_learner . get_regression_weights.survival_tree_learner . get_rich_output_params . get_roc_curve_data . get_split_categories . get_split_feature . get_split_threshold . get_split_weights . get_stability_results . get_survival_curve . get_survival_curve_data . get_survival_expected_time . get_survival_hazard . get_train_errors . get_tree . get_upper_child . glmnetcv_classifier . glmnetcv_regressor . glmnetcv_survival_learner . grid_search . iai_setup . imputation_learner . impute . impute_cv . install_julia . install_system_image . is_categoric_split . is_hyperplane_split . is_leaf . is_mixed_ordinal_split . is_mixed_parallel_split . is_ordinal_split . is_parallel_split . load_graphviz . mean_imputation_learner . missing_goes_lower . multi_questionnaire.default . multi_questionnaire.grid_search . multi_questionnaire . multi_tree_plot.default . multi_tree_plot.grid_search . multi_tree_plot . numeric_classification_reward_estimator . numeric_regression_reward_estimator . numeric_reward_estimator . numeric_survival_reward_estimator . opt_knn_imputation_learner . opt_svm_imputation_learner . opt_tree_imputation_learner . optimal_feature_selection_classifier . optimal_feature_selection_regressor . optimal_tree_classifier . optimal_tree_multi_classifier . optimal_tree_multi_regressor . optimal_tree_policy_maximizer . optimal_tree_policy_minimizer . optimal_tree_prescription_maximizer . optimal_tree_prescription_minimizer . optimal_tree_regressor . optimal_tree_survival_learner . optimal_tree_survivor . plot.grid_search . plot.roc_curve . plot.similarity_comparison . plot.stability_analysis . predict.categorical_reward_estimator . predict.glmnetcv_learner . predict.numeric_reward_estimator . predict . predict.optimal_feature_selection_learner . predict.supervised_learner . predict.supervised_multi_learner . predict.survival_learner . predict_expected_survival_time.glmnetcv_survival_learner . predict_expected_survival_time . predict_expected_survival_time.survival_curve . predict_expected_survival_time.survival_learner . predict_hazard.glmnetcv_survival_learner . predict_hazard . predict_hazard.survival_learner . predict_outcomes . predict_outcomes.policy_learner . predict_outcomes.prescription_learner . predict_proba.classification_learner . predict_proba.classification_multi_learner . predict_proba.glmnetcv_classifier . predict_proba . predict_reward.categorical_reward_estimator . predict_reward.numeric_reward_estimator . predict_reward . predict_shap . predict_treatment_outcome . predict_treatment_outcome_standard_error . predict_treatment_rank . print_path . prune_trees . questionnaire . questionnaire.optimal_feature_selection_learner . questionnaire.tree_learner . rand_imputation_learner . random_forest_classifier . random_forest_regressor . random_forest_survival_learner . read_json . refit_leaves . release_license . reset_display_label . resume_from_checkpoint . reward_estimator . roc_curve.classification_learner . roc_curve.classification_multi_learner . roc_curve.default . roc_curve.glmnetcv_classifier . roc_curve . score.categorical_reward_estimator . score.default . score.glmnetcv_learner . score.numeric_reward_estimator . score . score.optimal_feature_selection_learner . score.supervised_learner . score.supervised_multi_learner . set_display_label . set_julia_seed . set_params . set_reward_kernel_bandwidth . set_rich_output_param . set_threshold . show_in_browser.abstract_visualization . show_in_browser . show_in_browser.roc_curve . show_in_browser.tree_learner . show_questionnaire . show_questionnaire.optimal_feature_selection_learner . show_questionnaire.tree_learner . similarity_comparison . single_knn_imputation_learner . split_data . stability_analysis . transform . transform_and_expand . tree_plot . tune_reward_kernel_bandwidth . variable_importance.learner . variable_importance . variable_importance.optimal_feature_selection_learner . variable_importance.tree_learner . variable_importance_similarity . write_booster . write_dot . write_html.abstract_visualization . write_html . write_html.roc_curve . write_html.tree_learner . write_json . write_pdf . write_png . write_questionnaire . write_questionnaire.optimal_feature_selection_learner . write_questionnaire.tree_learner . write_svg . xgboost_classifier . xgboost_regressor . xgboost_survival_learner . zero_imputation_learner .
Some associated R codes: generic.R . heuristics.R . iaibase.R . iaitrees.R . install.R . interface.R . interface_class.R . optimalfeatureselection.R . optimaltrees.R . optimpute.R . rewardestimation.R . utils.R . Full iai package functions and examples
Downloads during the last 30 days
Get rewarded with contribution points by
helping add
Reviews / comments / questions /suggestions ↴↴↴
Today's Hot Picks in Authors and Packages
mistral
Various reliability analysis methods for rare event inference (computing failure probability and qua ...
Download / Learn more Package Citations See dependency
Download / Learn more Package Citations See dependency
Maintainer: Bertrand Iooss (view profile)
rdbnomics
R access to hundreds of millions data series from DBnomics API
(). ...
Download / Learn more Package Citations See dependency
Download / Learn more Package Citations See dependency
Maintainer: Sebastien Galais (view profile)
steepness
The steepness package computes steepness as a property of dominance hierarchies. Steepness is define ...
Download / Learn more Package Citations See dependency
Download / Learn more Package Citations See dependency
Maintainer: David Leiva (view profile)
critpath
Solving the problem of project management using CPM (Critical Path Method), PERT (Program Evaluation ...
Download / Learn more Package Citations See dependency
Download / Learn more Package Citations See dependency
Maintainer: Adam Kucharski (view profile)
quickcode
The NOT functions, 'R' tricks and a compilation of some simple quick plus often used 'R' codes to im ...
Download / Learn more Package Citations See dependency
Download / Learn more Package Citations See dependency
Maintainer: Obinna Obianom (view profile)
ftaproxim
Calculation and plotting of instantaneous unavailabilities of basic events along with the top event ...
Download / Learn more Package Citations See dependency
Download / Learn more Package Citations See dependency
Maintainer: Hossein Haghbin (view profile)
22,114
R Packages
188,080
Dependencies
55,244
Author Associations
22,115
Publication Badges
© Copyright 2022 - present. All right reserved, rpkg.net. Contact Us / Suggestions / Concerns