R: Leveraging Experiment Lines to Data Analytics

# Leveraging Experiment Lines to Data Analytics

## Documentation for package ‘daltoolbox’ version 1.0.767

- DESCRIPTION file.

## Help Pages

A B C D E F I K M O P R S T Z misc

## -- A --

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
adjust_ts_data | adjust 'ts_data'
autoenc_encode | Autoencoder - Encode
autoenc_encode_decode | Autoencoder - Encode

## -- B --

Boston | Boston Housing Data (Regression)

## -- C --

categ_mapping | Categorical mapping
classification | classification
cla_dtree | Decision Tree for classification
cla_knn | K Nearest Neighbor Classification
cla_majority | Majority Classification
cla_mlp | MLP for classification
cla_nb | Naive Bayes Classifier
cla_rf | Random Forest for classification
cla_svm | SVM for classification
cla_tune | Classification Tune
cluster | Cluster
clusterer | Clusterer
cluster_dbscan | DBSCAN
cluster_kmeans | k-means
cluster_pam | PAM
clu_tune | Clustering Tune

## -- D --

dal_base | Class dal_base
dal_learner | DAL Learner
dal_transform | DAL Transform
dal_tune | DAL Tune
data_sample | Data Sample
do_fit | do fit for time series
do_predict | do predict for time series
dt_pca | PCA

## -- E --

evaluate | evaluate

## -- F --

fit | Fit
fit.cla_tune | tune hyperparameters of ml model
fit.cluster_dbscan | fit dbscan model
fit_curvature_max | maximum curvature analysis
fit_curvature_min | minimum curvature analysis

## -- I --

inverse_transform | Inverse Transform

## -- K --

k_fold | k-fold sampling

## -- M --

minmax | min-max normalization
MSE.ts | MSE

## -- O --

outliers | Outliers

## -- P --

plot_bar | plot bar graph
plot_boxplot | plot boxplot
plot_boxplot_class | plot 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 a time series chart
plot_ts_pred | Plot a time series chart
predictor | DAL Predict

## -- R --

R2.ts | R2
regression | Regression
reg_dtree | Decision Tree for regression
reg_knn | knn regression
reg_mlp | MLP for regression
reg_rf | Random Forest for regression
reg_svm | SVM for regression
reg_tune | Regression Tune

## -- S --

sample_random | Sample Random
sample_stratified | sample_stratified
select_hyper | Selection hyper parameters
select_hyper.cla_tune | selection of hyperparameters
select_hyper.ts_tune | selection of hyperparameters (time series)
set_params | Assign parameters
set_params.default | Assign parameters
sin_data | Time series example dataset
sMAPE.ts | sMAPE
smoothing | Smoothing
smoothing_cluster | Smoothing by cluster
smoothing_freq | Smoothing by Freq
smoothing_inter | Smoothing by interval

## -- T --

train_test | training and test
train_test_from_folds | k-fold training and test partition object
transform | Transform
ts_arima | ARIMA
ts_conv1d | Conv1D
ts_data | ts_data
ts_elm | ELM
ts_head | ts_head
ts_knn | knn time series prediction
ts_lstm | LSTM
ts_mlp | MLP
ts_norm_an | Time Series Adaptive Normalization
ts_norm_diff | Time Series Diff
ts_norm_ean | Time Series Adaptive Normalization (Exponential Moving Average - EMA)
ts_norm_gminmax | Time Series Global Min-Max
ts_norm_swminmax | Time Series Sliding Window Min-Max
ts_projection | Time Series Projection
ts_reg | TSReg
ts_regsw | TSRegSW
ts_rf | Random Forest
ts_sample | Time Series Sample
ts_svm | SVM
ts_tune | Time Series Tune

## -- Z --

zscore | z-score normalization

## -- misc --

[.ts_data | Extract a subset of a time series stored in an object