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daltoolbox  

Leveraging Experiment Lines to Data Analytics
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("daltoolbox", "1.2.747")



Attach the package and use:
library("daltoolbox")
Maintained by
Eduardo Ogasawara
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2023-06-30
Latest Update: 2025-06-28
Description:
The natural increase in the complexity of current research experiments and data demands better tools to enhance productivity in Data Analytics. The package is a framework designed to address the modern challenges in data analytics workflows. The package is inspired by Experiment Line concepts. It aims to provide seamless support for users in developing their data mining workflows by offering a uniform data model and method API. It enables the integration of various data mining activities, including data preprocessing, classification, regression, clustering, and time series prediction. It also offers options for hyper-parameter tuning and supports integration with existing libraries and languages. Overall, the package provides researchers with a comprehensive set of functionalities for data science, promoting ease of use, extensibility, and integration with various tools and libraries. Information on Experiment Line is based on Ogasawara et al. (2009) .
How to cite:
Eduardo Ogasawara (2023). daltoolbox: Leveraging Experiment Lines to Data Analytics. R package version 1.2.747, https://cran.r-project.org/web/packages/daltoolbox. Accessed 05 Aug. 2026.
Previous versions and publish date:
(2026-07-09 19:50), 1.0.77 (2023-06-30 13:40), 1.0.707 (2023-07-18 05:10), 1.0.717 (2023-07-22 12:40), 1.0.727 (2023-10-25 23:40), 1.0.747 (2024-03-25 08:20), 1.0.767 (2024-04-01 00:30), 1.0.787 (2024-11-03 06:30), 1.1.727 (2024-11-25 06:10), 1.1.737 (2025-04-21 09:00), 1.1.747 (2025-04-28 15:30), 1.2.707 (2025-05-13 08:20), 1.2.717 (2025-06-22 00:00), 1.2.727 (2025-06-28 18:20), 1.2.737 (2025-08-20 19:00), 1.2.747 (2025-10-27 07:10), 1.3.717 (2026-02-10 07:10), 1.3.727 (2026-03-12 07:10), 1.3.747 (2026-05-14 07:30)
Other packages that cited daltoolbox R package
View daltoolbox citation profile
Other R packages that daltoolbox depends, imports, suggests or enhances
Complete documentation for daltoolbox
Functions, R codes and Examples using the daltoolbox R package
Some associated functions: Boston . MSE.ts . action.dal_transform . action . adjust_class_label . adjust_data.frame . adjust_factor . adjust_matrix . adjust_ts_data . autoenc_encode . autoenc_encode_decode . categ_mapping . cla_dtree . cla_knn . cla_majority . cla_mlp . cla_nb . cla_rf . cla_svm . cla_tune . classification . clu_tune . cluster . cluster_dbscan . cluster_kmeans . cluster_pam . clusterer . dal_base . dal_learner . dal_transform . dal_tune . data_sample . do_fit . do_predict . dt_pca . evaluate . fit.cla_tune . fit.cluster_dbscan . fit . fit_curvature_max . fit_curvature_min . inverse_transform . k_fold . minmax . outliers . plot_bar . plot_boxplot . plot_boxplot_class . plot_density . plot_density_class . plot_groupedbar . plot_hist . plot_lollipop . plot_pieplot . plot_points . plot_radar . plot_scatter . plot_series . plot_stackedbar . plot_ts . plot_ts_pred . predictor . reg_dtree . reg_knn . reg_mlp . reg_rf . reg_svm . reg_tune . regression . sMAPE.ts . sample_random . sample_stratified . select_hyper.cla_tune . select_hyper . select_hyper.ts_tune . set_params.default . set_params . sin_data . smoothing . smoothing_cluster . smoothing_freq . smoothing_inter . sub-.ts_data . train_test . train_test_from_folds . transform . ts_arima . ts_conv1d . ts_data . ts_elm . ts_head . ts_knn . ts_lstm . ts_mlp . ts_norm_an . ts_norm_diff . ts_norm_ean . ts_norm_gminmax . ts_norm_swminmax . ts_projection . ts_reg . ts_regsw . ts_rf . ts_sample . ts_svm . ts_tune . zscore . 
Some associated R codes: cla_classification.R . cla_dtree.R . cla_knn.R . cla_majority.R . cla_mlp.R . cla_nb.R . cla_rf.R . cla_svm.R . cla_tune.R . clu_clusterer.R . clu_dbscan.R . clu_kmeans.R . clu_pam.R . clu_tune.R . dal_adjust.R . dal_base.R . dal_learner.R . dal_predictor.R . dal_tune.R . data.R . globals.R . graphics.R . reg_dtree.R . reg_knn.R . reg_mlp.R . reg_regression.R . reg_rf.R . reg_svm.R . reg_tune.R . trans_autoenc_encode.R . trans_autoenc_encode_decode.R . trans_categ_mapping.R . trans_dt_pca.R . trans_fit_curvature_max.R . trans_fit_curvature_min.R . trans_norm_minmax.R . trans_norm_zscore.R . trans_outliers.R . trans_sample.R . trans_sample_random.R . trans_sample_strat.R . trans_smoothing.R . trans_smoothing_cluster.R . trans_smoothing_freq.R . trans_smoothing_inter.R . trans_transform.R . ts_arima.R . ts_conv1d.R . ts_data.R . ts_elm.R . ts_knn.R . ts_lstm.R . ts_mlp.R . ts_norm_an.R . ts_norm_diff.R . ts_norm_ean.R . ts_norm_gminmax.R . ts_norm_swminmax.R . ts_projection.R . ts_reg.R . ts_regsw.R . ts_rf.R . ts_sample.R . ts_svm.R . ts_tune.R .  Full daltoolbox package functions and examples
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