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-decode |
Boston | Boston Housing Data (Regression) |
categ_mapping | Categorical mapping |
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 |
classification | classification |
cla_svm | SVM for classification |
cla_tune | Classification Tune |
cluster | Cluster |
cluster_dbscan | DBSCAN |
clusterer | Clusterer |
cluster_kmeans | k-means |
cluster_pam | PAM |
clu_tune | Clustering Tune |
dal_base | Class dal_base |
dal_learner | DAL Learner |
dal_transform | DAL Transform |
dal_tune | DAL Tune |
data_sample | Data Sample |
do_fit | Fit Time Series Model |
do_predict | Predict Time Series Model |
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 |
fit_curvature_min | minimum curvature analysis |
inverse_transform | Inverse Transform |
k_fold | K-fold sampling |
minmax | Min-max normalization |
MSE.ts | MSE |
outliers | Outliers |
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 a time series chart with predictions |
predictor | DAL Predict |
R2.ts | R2 |
reg_dtree | Decision Tree for regression |
reg_knn | knn regression |
reg_mlp | MLP for regression |
regression | Regression |
reg_rf | Random Forest for regression |
reg_svm | SVM for regression |
reg_tune | Regression Tune |
sample_random | Sample Random |
sample_stratified | Stratified Random Sampling |
select_hyper | Selection hyper parameters |
select_hyper.cla_tune | selection of hyperparameters |
select_hyper.ts_tune | Select Optimal Hyperparameters for Time Series Models |
set_params | Assign parameters |
set_params.default | 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 |
sub-.ts_data | Subset Extraction for Time Series Data |
train_test | Train-Test Partition |
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 | Extract the First Observations from a 'ts_data' Object |
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... |
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 |
zscore | Z-score normalization |
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