| bandwidth_rot | MASS' Rule of Thumb Bandwidth Estimation |
| brewer.pal_extended | RColorBrewer's Extended Palettes without Warning |
| CascadeForest | Cascade Forest implementation in R |
| CascadeForest_pred | Cascade Forest Predictor implementation in R |
| cbindlist | data.table column list binding |
| CRTreeForest | Complete-Random Tree Forest implementation in R |
| CRTreeForest_pred | Complete-Random Tree Forest Predictor implementation in R |
| CRTree_Forest_pred_internals | Complete-Random Tree Forest Predictor (Deferred predictor)... |
| df_acc | Accuracy loss (Acc) (computation function, any size) |
| df_acc_bin | Accuracy loss (Acc) (computation function, binary... |
| df_auc | Area Under the Curve Loss (AUC) (computation function, any... |
| df_logloss | Logarithmic Loss (Logloss) (computation function, any size) |
| df_mae | Mean Absolute Error (MAE) (computation function, any size) |
| df_mape | Mean Absolute Percentage Error (MAPE) (computation function,... |
| df_mce | Mean Cubic Error (MCE) (computation function, any size) |
| df_medae | Median Absolute Error (MedAE) (computation function, single... |
| df_medpae | Median Absolute Percentage Error (MedPAE) (computation... |
| df_mse | Mean Squared Error (MSE) (computation function, any size) |
| df_r | Pearson Coefficient of Correlation (R) (computation function,... |
| df_r2 | Coefficient of Determination (R^2) (computation function, any... |
| df_rmse | Root Mean Squared Error (RMSE) (computation function, any... |
| df_spearman | Spearman Coefficient of Correlation (R) (computation... |
| DT2mat | data.table to matrix |
| DTcbind | data.table column binding (nearly without) copy |
| DTcolsample | data.table colsampling (nearly without) copy |
| DTfillNA | data.table NA fill (nearly without) copy (or data.frame) |
| DTrbind | data.table row binding (nearly without) copy |
| DTsubsample | data.table subsampling (nearly without) copy |
| ExtraOpt | Cross-Entropy -based Hybrid Optimization |
| FastROC | Fast AUROC (AUC, ROC) computation |
| FeatureLookup | The Non-Linear Feature Engineering Assistant |
| get.max_acc | Maximum binary accuracy |
| get.max_f1 | Maximum F1 Score (Precision with Sensitivity harmonic mean) |
| get.max_fallout | Minimum Fall-Out (False Positive Rate) |
| get.max_kappa | Maximum Kappa statistic |
| get.max_mcc | Maximum Matthews Correlation Coefficient |
| get.max_missrate | Minimum Miss-Rate (False Negative Rate) |
| get.max_precision | Maximum Precision (Positive Predictive Value) |
| get.max_sensitivity | Maximum Sensitivity (True Positive Rate) |
| get.max_specificity | Maximum Specificity (True Negative Rate) |
| GetPartyRules | partykit's Party Rules to data.table |
| grid_arrange_shared_legend | ggplot multiple plot per page |
| interactive.eda_d3js | Interactive Dashboard for Exploratory Data Analysis (d3js) |
| interactive.eda_ggplot | Interactive Dashboard for Exploratory Data Analysis (ggplot) |
| interactive.eda_plotly | Interactive Dashboard for Exploratory Data Analysis (Plotly) |
| interactive.eda_RColorBrewer | Interactive Dashboard for Finding the Perfect Color Brewer... |
| interactive.eda_tree | Interactive Dashboard for the Non-Linear Feature Engineering... |
| interactive.SymbolicLoss | Interactive Dashboard for Symbolic Gradient/Hessian Loss... |
| kernel2d_est | MASS' Two-Dimensional Kernel Density Estimation |
| kfold | (Un)Stratified k-fold for any type of label |
| Laurae_load | Laurae Package Loader |
| LauraeML | Laurae's Machine Learning (Automated modeling, Automated... |
| LauraeML_gblinear | Laurae's Machine Learning (xgboost gblinear helper function) |
| LauraeML_gblinear_par | Laurae's Machine Learning (xgboost gblinear helper parallel... |
| LauraeML_lgbreg | Laurae's Machine Learning (LightGBM regression helper... |
| LauraeML_utils.badlog | Laurae's Machine Learning Utility: bad input logger |
| LauraeML_utils.badscore | Laurae's Machine Learning Utility: bad input score |
| LauraeML_utils.feat_sel | Laurae's Machine Learning Utility: subset features to select... |
| LauraeML_utils.lgb_data | Laurae's Machine Learning Utility: create LightGBM dataset |
| LauraeML_utils.newlog | Laurae's Machine Learning Utility: new input logger |
| LauraeML_utils.xgb_data | Laurae's Machine Learning Utility: create xgboost dataset |
| Laurae-package | Laurae's package for (very) advanced Data Science for R |
| Lextravagenza | Laurae's Extravagenza machine learning model |
| lgbm.cv | LightGBM Cross-Validated Model Training |
| lgbm.cv.prep | LightGBM Cross-Validated Model Preparation |
| lgbm.fi | LightGBM Feature Importance |
| lgbm.find | Find LightGBM Path |
| lgbm.fi.plot | LightGBM Feature Importance Plotting |
| lgbm.metric | LightGBM Metric Output |
| lgbm.predict | LightGBM Prediction |
| lgbm.train | LightGBM Model Training |
| LogLoss | Fast Logarithmic Loss (logloss) computation |
| loss_LKL | Laurae's Kullback-Leibler Error (computation function) |
| loss_LKL_grad | Laurae's Kullback-Leibler Error (gradient function) |
| loss_LKL_hess | Laurae's Kullback-Leibler Error (hessian function) |
| loss_LKL_math | Laurae's Kullback-Leibler Error (math function) |
| loss_LKL_xgb | Laurae's Kullback-Leibler Error (xgboost function) |
| loss_LL | Loglikelihood Error (computation function) |
| loss_LL_grad | Loglikelihood Error (gradient function) |
| loss_LL_hess | Loglikelihood Error (hessian function) |
| loss_LL_math | Loglikelihood Error (math function) |
| loss_LL_xgb | Loglikelihood Error (xgboost function) |
| loss_MAE | Mean Absolute Error (computation function) |
| loss_MAE_grad | Mean Absolute Error (gradient function) |
| loss_MAE_hess | Mean Absolute Error (hessian function) |
| loss_MAE_math | Mean Absolute Error (symbolic function) |
| loss_MAE_xgb | Mean Absolute Error (xgboost function) |
| loss_MCE | Mean Cubic Error (computation function) |
| loss_MCE_grad | Mean Cubic Error (gradient function) |
| loss_MCE_hess | Mean Cubic Error (hessian function) |
| loss_MCE_math | Mean Cubic Error (math function) |
| loss_MCE_xgb | Mean Cubic Error (xgboost function) |
| loss_MSE | Mean Squared Error (computation function) |
| loss_MSE_grad | Mean Squared Error (gradient function) |
| loss_MSE_hess | Mean Squared Error (hessian function) |
| loss_MSE_math | Mean Squared Error (symbolic function) |
| loss_MSE_xgb | Mean Squared Error (xgboost function) |
| loss_Poisson | Laurae's Poisson Error (computation function) |
| loss_Poisson_grad | Laurae's Poisson Error (gradient function) |
| loss_Poisson_hess | Laurae's Poisson Error (hessian function) |
| loss_Poisson_math | Laurae's Poisson Error (math function) |
| loss_Poisson_xgb | Laurae's Poisson Error (xgboost function) |
| mean2 | Fast mean computation |
| MGScanning | Multi-Grained Scanning implementation in R |
| MGScanning_pred | Multi-Grained Scanning Predictor implementation in R |
| nkfold | (Un)Stratified Repeated k-fold for any type of label |
| partial_dep.feature | Partial Dependency, output analyzer |
| partial_dep.obs | Partial Dependency Observation, Contour (single observation) |
| partial_dep.obs_all | Partial Dependency Observation, Contour (multiple... |
| partial_dep.plot | Partial Dependency, plotting function |
| plotting.max_acc | Maximum binary accuracy plotting |
| plotting.max_f1 | Maximum F1 Score (Precision with Sensitivity harmonic mean)... |
| plotting.max_fallout | Minimum Fall-Out (False Positive Rate) plotting |
| plotting.max_kappa | Maximum Kappa statistic plotting |
| plotting.max_mcc | Maximum Matthews Correlation Coefficient plotting |
| plotting.max_missrate | Minimum Miss-Rate (False Negative Rate) plotting |
| plotting.max_precision | Maximum Precision (Positive Predictive Value) plotting |
| plotting.max_sensitivity | Maximum Sensitivity (True Positive Rate) plotting |
| plotting.max_specificity | Maximum Specificity (True Negative Rate) plotting |
| predictor_xgb | Partial Dependency, xgboost predictor |
| pred.Lextravagenza | Laurae's Extravagenza machine learning model prediction |
| print_fp | Print appropriately formatted fixed point |
| print_hyb | Print appropriately formatted integer or fixed point (hybrid) |
| print_int | Print appropriately formatted integer |
| print_multi | Print appropriately formatted hyperparameters and error |
| prob.max_acc | Probability binary accuracy |
| prob.max_f1 | Probability F1 Score (Precision with Sensitivity harmonic... |
| prob.max_fallout | Probability Fall-Out (False Positive Rate) |
| prob.max_kappa | Probability Kappa statistic |
| prob.max_mcc | Probability Matthews Correlation Coefficient |
| prob.max_missrate | Probability Miss-Rate (False Negative Rate) |
| prob.max_precision | Probability Precision (Positive Predictive Value) |
| prob.max_sensitivity | Probability Sensitivity (True Positive Rate) |
| prob.max_specificity | Probability Specificity (True Negative Rate) |
| read_sparse_csv | Read sparse (numeric) CSVs |
| report.lm | Linear Regression Modeling HTML report |
| report.xgb | Extreme Gradient Boosting HTML report |
| report.xgb.helper | Extreme Gradient Boosting HTML report helper function |
| rule_double | Outlying bivariate linear continuous association rule finder |
| rule_single | Outlying univariate continuous association rule finder |
| setDF | Convert data.table to data.frame without copy |
| stat_smooth_func | ggplot facet function with printed formula (non Plotly) |
| stat_smooth_func.plotly | ggplot facet function with printed formula (Plotly) |
| SymbolicLoss | Symbolic Gradient/Hessian Loss computation |
| tableplot_jpg | Batch tableplot generator to JPEG |
| timer | Get current Time in Milliseconds |
| timer_func | Get Function Time in Milliseconds |
| timer_func_print | Get Function Time in Milliseconds (with printing) |
| tsne_grid | t-SNE grid search function |
| xgb.importance.interactive | xgboost feature importance interactive table |
| xgb.max_acc | xgboost evaluation metric for maximum binary accuracy |
| xgb.max_f1 | xgboost evaluation metric for maximum F1 Score (Precision... |
| xgb.max_fallout | xgboost evaluation metric for minimum Fall-Out (False... |
| xgb.max_kappa | xgboost evaluation metric for maximum Kappa statistic |
| xgb.max_mcc | xgboost evaluation metric for maximum Matthews Correlation... |
| xgb.max_missrate | xgboost evaluation metric for minimum Miss-Rate (False... |
| xgb.max_precision | xgboost evaluation metric for maximum Precision (Positive... |
| xgb.max_sensitivity | xgboost evaluation metric for maximum Sensitivity (True... |
| xgb.max_specificity | xgboost evaluation metric for maximum Specificity (True... |
| xgb.ncv | xgboost repeated cross-validation (Repeated k-fold) |
| xgboard.dump | Xgboard Dumper |
| xgboard.eval.error | Xgboard Metric Evaluation Error (Binary Accuracy) |
| xgboard.eval.logloss | Xgboard Metric Evaluation Logloss (Binary Logloss) |
| xgboard.init | Xgboard Metric Evaluation Initialization (Environment) |
| xgboard.run | Xgboard Server Launcher (Web Interface Creator) |
| xgboard.time | Xgboard Metric Evaluation Time Reset (Environment) |
| xgboard.xgb | Xgboard Metric Evaluation Creator (Wrapper) |
| xgb.opt.depth | xgboost depth automated optimizer |
