## ----setup, include = FALSE--------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>" ) ## ---- include=FALSE, warning=FALSE, error=FALSE, message=FALSE---------------- library("ggplot2") ## ---- warning = FALSE, echo = FALSE, message = FALSE, include = TRUE---------- library("DALEX") data(apartments) head(apartments) ## ---- warning = FALSE, error = FALSE, message = FALSE, include = TRUE--------- library("randomForest") apartments_rf_model <- randomForest(m2.price ~ construction.year + surface + floor + no.rooms, data = apartments) explainer_rf <- explain(apartments_rf_model, data = apartmentsTest[,2:5], y = apartmentsTest$m2.price) ## ---- warning = FALSE, error = FALSE, message = FALSE, include = TRUE--------- new_apartment <- data.frame(construction.year = 1998, surface = 88, floor = 2L, no.rooms = 3) predict(apartments_rf_model, new_apartment) ## ---- warning = FALSE, error = FALSE, message = FALSE, include = TRUE--------- library("ingredients") profiles <- predict_profile(explainer_rf, new_apartment) plot(profiles) + show_observations(profiles) ## ---- warning = FALSE, error = FALSE, message = FALSE, include = TRUE--------- library("vivo") measure <- local_variable_importance(profiles, apartments[,2:5], absolute_deviation = TRUE, point = TRUE, density = TRUE) ## ---- warning = FALSE, error = FALSE, message = FALSE, include = TRUE--------- plot(measure) ## ---- warning = FALSE, error = FALSE, message = FALSE, include = TRUE--------- measure_2 <- local_variable_importance(profiles, apartments[,2:5], absolute_deviation = FALSE, point = TRUE, density = TRUE) measure_3 <- local_variable_importance(profiles, apartments[,2:5], absolute_deviation = FALSE, point = TRUE, density = FALSE) ## ---- warning = FALSE, error = FALSE, message = FALSE, include = TRUE--------- plot(measure, measure_2, measure_3, color = "_label_method_") ## ---- warning = FALSE, error = FALSE, message = FALSE, include = TRUE--------- plot(measure, measure_2, measure_3, color = "_label_method_", type = "lines") ## ---- warning = FALSE, error = FALSE, message = FALSE, include = TRUE--------- apartments_lm_model <- lm(m2.price ~ construction.year + surface + floor + no.rooms, data = apartments) explainer_lm <- explain(apartments_lm_model, data = apartmentsTest[,2:5], y = apartmentsTest$m2.price) ## ---- warning = FALSE, error = FALSE, message = FALSE, include = TRUE--------- profiles_lm <- predict_profile(explainer_lm, new_apartment) measure_lm <- local_variable_importance(profiles_lm, apartments[,2:5], absolute_deviation = TRUE, point = TRUE, density = TRUE) ## ---- warning = FALSE, error = FALSE, message = FALSE, include = TRUE--------- plot(measure, measure_lm, color = "_label_model_", type = "lines")