In rsquaredacademy/report: Generate Reports from Rsquared Academy Packages

knitr::opts_chunk$set(echo = FALSE)

suppressWarnings(suppressMessages(library(blorr, quietly = TRUE)))
suppressWarnings(suppressMessages(library(magrittr, quietly = TRUE)))
suppressWarnings(suppressMessages(library(purrr, quietly = TRUE)))
suppressWarnings(suppressMessages(library(rlang, quietly = TRUE)))

report_data <- model$data
is_fact <- map_lgl(report_data, is.factor)
fact_df <- report_data[, is_fact]
response <- names(model.frame(model))[1]
predictors <- names(fact_df)                          

Bivariate Analysis

blr_bivariate_analysis(report_data, !!sym(response), !!!predictors)

Weight of Evidence & Information Value

blr_woe_iv_stats(report_data, !!sym(response), !!!predictors)

Regression Output

blr_regress(model)

Stepwise Selection

blr_step_aic_both(model)

Plot

model %>%
  blr_step_aic_both() %>%
  plot()

Model Fit Statistics

blr_model_fit_stats(model)

Confusion Matrix

blr_confusion_matrix(model, cutoff = 0.5)

Hosmer Lemeshow Test

blr_test_hosmer_lemeshow(model)

Gains Table

blr_gains_table(model)

Lift Chart

model %>%
    blr_gains_table() %>%
    plot()

ROC Curve

model %>%
    blr_gains_table() %>%
  blr_roc_curve()

KS Chart

model %>%
    blr_gains_table() %>%
  blr_ks_chart()

Decile Lift Chart

model %>%
  blr_gains_table() %>%
  blr_decile_lift_chart()

Capture Rate by Decile

model %>%
  blr_gains_table() %>%
  blr_decile_capture_rate()

Lorenz Curve

blr_lorenz_curve(model)

Influence Diagnostics

blr_plot_diag_influence(model)

Leverage Diagnostics

blr_plot_diag_leverage(model)

Fitted Values Diagnostics

blr_plot_diag_fit(model)

rsquaredacademy/report documentation built on Sept. 29, 2019, 12:14 a.m.