aider_theme | Aider ggplot2 theme |
analyse_interactions | Find meaningfull interactions |
analyse_missing | Analyse missing values |
analyse_predictiveness | Analyse variables predictiveness |
analyse_transformations | Find predictive variable transformations |
apply_mov | Apply multivariate outlier detection |
apply_recipe | Apply a model recipe |
apply_rfe | Apply recursive feature elimination |
assess_performance | Assess model performance |
calculate_bad_rate | Calculate bad rate |
calculate_correlation | Calculate tidy correlation |
calculate_decile_table | Calculate a decile breakdown |
calculate_importance | Find the most important variables |
calculate_logodds_table | Calculate a log-odds table |
calculate_share | Calcuate grand total share |
calculate_stats_numeric | Calculate statistics of numerical attributes |
calibrate_probabilities | This function calibrates model predicted probabilities by... |
cap_at_percentile | Cap numeric values at selected percentiles |
cap_between | Cap numeric values between two values |
change_names | Change a vector or data frame names |
count_proportions | Count proportions of levels |
count_unique | Count unique observations |
first_to_lower | Convert strings first letter to lowercase |
first_to_upper | Convert strings first letter to uppercase |
format_my_table | Format a knitr table nicely |
lookup | Perform vlookups similar as in Excel |
number_ticks | Equal sized axis ticks |
plot_bars | Plot bar-plots of numerical variables |
plot_boxplot | Plot box-plots of numerical variables |
plot_calibration | Plot a calibration plot of model performance |
plot_correlation | Plot a correlation matrix of numerical variables |
plot_deciles | Plot decile plots of numerical variables |
plot_density | Plot density of numerical variables |
plot_line | Plot lines of numerical variables. Usefull especially for... |
plot_logodds | Plot a log-odds table |
round_to | Round values to integers |
select_palette | Palettes are based on the list of available color schemes:... |
set_me_up | Basic R session setup |
train_model | Train various predictive models |
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