knitr::opts_chunk$set( collapse = TRUE, comment = "#>", message = FALSE, eval = FALSE )
library(arenar) apartments <- DALEX::apartments head(apartments)
Let's compare three models: GLM and GBMs with 100 and 500 trees. For each we create explainer from DALEX package.
library(gbm) library(DALEX) library(dplyr) model_gbm100 <- gbm(m2.price ~ ., data = apartments, n.trees = 100) expl_gbm100 <- explain( model_gbm100, data = apartments, y = apartments$m2.price, label = "gbm [100 trees]" ) model_gbm500 <- gbm(m2.price ~ ., data = apartments, n.trees = 500) expl_gbm500 <- explain( model_gbm500, data = apartments, y = apartments$m2.price, label = "gbm [500 trees]" ) model_glm <- glm(m2.price ~ ., data = apartments) expl_glm <- explain(model_glm, data = apartments, y = apartments$m2.price)
Plots for static Arena are pre-caluclated and it takes time and file size. For example we will take only apartments from 2009 or newer. Random sample is also good.
observations <- apartments %>% filter(construction.year >= 2009) # Observations' names are taken from rownames rownames(observations) <- paste0( observations$district, " ", observations$surface, "m2 " )
arena <- create_arena() %>% # Pushing explainers for each models push_model(expl_gbm100) %>% push_model(expl_gbm500) %>% push_model(expl_glm) %>% # Push dataframe of observations push_observations(observations) %>% # Upload calculated arena files to Gist and open Arena in browser upload_arena()
There are two ways of add new observations or new models without recalcualating already generated plots. Let's add apartments built in 2008. It's similar for models.
observations2 <- apartments %>% filter(construction.year == 2008) # Observations' names are taken from rownames rownames(observations2) <- paste0( observations2$district, " ", observations2$surface, "m2 " )
We can add observations to already existing arena object and call
arena %>% push_observations(observations2) %>% upload_arena()
Sometimes we don't want to close Arena session and just add data. There is
arena_upload function to do that. Remember to append new arena
object and to push all models and all observations that are required to plots
you want to append.
create_arena() %>% push_observations(arena_push_observations2) %>% push_model(expl_glm) %>% push_model(expl_gbm100) %>% push_model(expl_gbm500) %>% upload_arena(append_data = TRUE)
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