Leveraging Experiment Lines to Data Analytics

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Documentation for package ‘daltoolbox’ version 1.2.747

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action Action
action.dal_transform Action implementation for transform
adjust_class_label Adjust categorical mapping
adjust_data.frame Adjust to data frame
adjust_factor Adjust factors
adjust_matrix Adjust to matrix
autoenc_base_e Autoencoder base (encoder)
autoenc_base_ed Autoencoder base (encoder + decoder)
Boston Boston Housing Data (Regression)
categ_mapping Categorical mapping (one‑hot encoding)
classification Classification base class
cla_dtree Decision Tree for classification
cla_knn K-Nearest Neighbors (KNN) Classification
cla_majority Majority baseline classifier
cla_mlp MLP for classification
cla_nb Naive Bayes Classifier
cla_rf Random Forest for classification
cla_svm SVM for classification
cla_tune Classification tuning (k-fold CV)
cluster Cluster
clusterer Clusterer
cluster_dbscan DBSCAN
cluster_kmeans k-means
cluster_pam PAM (Partitioning Around Medoids)
clu_tune Clustering tuning (intrinsic metric)
dal_base Class dal_base
dal_graphics Graphics utilities
dal_learner DAL Learner (base class)
dal_transform DAL Transform
dal_tune DAL Tune (base for hyperparameter search)
data_sample Data sampling abstractions
dt_pca PCA
evaluate Evaluate
fit Fit
fit.cla_tune tune hyperparameters of ml model
fit.cluster_dbscan fit dbscan model
fit_curvature_max Maximum curvature analysis (elbow detection)
fit_curvature_min Minimum curvature analysis (elbow detection)
inverse_transform Inverse Transform
k_fold K-fold sampling
minmax Min-max normalization
outliers_boxplot Outlier removal by boxplot (IQR rule)
outliers_gaussian Outlier removal by Gaussian 3-sigma rule
plot_bar Plot bar graph
plot_boxplot Plot boxplot
plot_boxplot_class Boxplot per class
plot_density Plot density
plot_density_class Plot density per class
plot_groupedbar Plot grouped bar
plot_hist Plot histogram
plot_lollipop Plot lollipop
plot_pieplot Plot pie
plot_points Plot points
plot_radar Plot radar
plot_scatter Scatter graph
plot_series Plot series
plot_stackedbar Plot stacked bar
plot_ts Plot time series chart
plot_ts_pred Plot time series with predictions
predictor Predictor (base for classification/regression)
regression Regression base class
reg_dtree Decision Tree for regression
reg_knn K-Nearest Neighbors (KNN) Regression
reg_mlp MLP for regression
reg_rf Random Forest for regression
reg_svm SVM for regression
reg_tune Regression tuning (k-fold CV)
sample_random Random sampling
sample_stratified Stratified sampling
select_hyper Selection of hyperparameters
select_hyper.cla_tune selection of hyperparameters
set_params Assign parameters
set_params.default Default Assign parameters
smoothing Smoothing (binning/quantization)
smoothing_cluster Smoothing by clustering (k-means)
smoothing_freq Smoothing by equal frequency
smoothing_inter Smoothing by equal interval
train_test Train-Test Partition
train_test_from_folds k-fold training and test partition object
transform Transform
zscore Z-score normalization