Package | Purpose | Chapter(s) |
---|---|---|
BART | Bayesian additive trees | 10 |
broom | Tidy regression output | 5 |
CAM(^+) | Causal Additive Models | 15 |
caTools | AUC curves | 11 |
CausalImpact | Causal inference with structural time series | 15 |
cowplot | Stacking plots | 4 & 13 |
breakDown | Breakdown interpretability | 14 |
dummies | One-hot encoding | 8 |
e1071 | Support Vector Machines | 9 |
factoextra | PCA visualization | 16 |
fastAdaboost | Boosted trees | 7 |
forecast | Autocorrelation function | 4 |
FNN | Nearest Neighbors detection | 16 |
ggpubr | Combining plots | 11 |
glmnet | Penalized regressions | 6 |
iml | Interpretability tools | 14 |
keras | Neural networks | 8 |
lime | Interpretability | 14 |
lmtest | Granger causality | 15 |
lubridate | Handling dates | All (or many) |
naivebayes | Naive Bayes classifier | 10 |
pcalg | Causal graphs | 15 |
quadprog | Quadratic programming | 12 |
quantmod | Data extraction | 4, 12 |
randomForest | Random forests | 7 |
rBayesianOptimization | Bayesian hyperparameter tuning | 11 |
ReinforcementLearning | Reinforcement Learning | 17 |
Rgraphviz(^*) | Causal graphs | 15 |
rpart and rpart.plot | Simple decision trees | 7 |
spBayes | Bayesian linear regression | 10 |
tidyverse | Environment for data science, data wrangling | All |
xgboost | Boosted trees | 7 |
xtable | Table formatting | 4 |