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model_export.md

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model_export

First attach the randomForest package and load the model and test data.

suppressPackageStartupMessages(library("randomForest"))

lst <- readRDS("thRS500.RDS")
varslist <- lst$varslist
fmodel <- lst$fmodel
buzztest <- lst$buzztest
rm(list = "lst")

Now covert the model to SQL.

sql <- tidypredict::tidypredict_sql(
  fmodel,
  dbplyr::simulate_mssql())

length(sql)
## [1] 500

substr(sql[[1]], 1, 500)
## <SQL> CASE
## WHEN (`num.displays_06` >= 1517.5 AND `avg.auths.per.disc_00` < 2.25 AND `num.displays_06` < 2075.0) THEN ('0')
## WHEN (`num.displays_03` >= 1114.5 AND `atomic.containers_01` < 9.5 AND `avg.auths.per.disc_00` >= 2.25 AND `num.displays_06` < 2075.0) THEN ('0')
## WHEN (`num.authors.topic_04` >= 30.0 AND `atomic.containers_01` >= 9.5 AND `avg.auths.per.disc_00` >= 2.25 AND `num.displays_06` < 2075.0) THEN ('1')
## WHEN (`num.displays_07` >= 51210.0 AND `attention.level.author_01` < 0.0136155 AND `num

substr(sql[[2]], 1, 200)
## <SQL> CASE
## WHEN (`number.total.disc_07` >= 3.5 AND `attention.level.author_00` < 0.0004155 AND `num.displays_06` < 2110.5) THEN ('0')
## WHEN (`attention.level.author_04` < 0.0035865 AND `attention.level.autho

# From: https://shiring.github.io/machine_learning/2017/03/16/rf_plot_ggraph

library(dplyr)
## Warning: package 'dplyr' was built under R version 3.5.2

## 
## Attaching package: 'dplyr'

## The following object is masked from 'package:randomForest':
## 
##     combine

## The following objects are masked from 'package:stats':
## 
##     filter, lag

## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union

library(ggraph)
## Loading required package: ggplot2

## Warning: package 'ggplot2' was built under R version 3.5.2

## 
## Attaching package: 'ggplot2'

## The following object is masked from 'package:randomForest':
## 
##     margin

library(igraph)
## Warning: package 'igraph' was built under R version 3.5.2

## 
## Attaching package: 'igraph'

## The following objects are masked from 'package:dplyr':
## 
##     as_data_frame, groups, union

## The following objects are masked from 'package:stats':
## 
##     decompose, spectrum

## The following object is masked from 'package:base':
## 
##     union

tree_func <- function(final_model, 
                      tree_num) {
  
  # get tree by index
  tree <- randomForest::getTree(final_model, 
                                k = tree_num, 
                                labelVar = TRUE) %>%
    tibble::rownames_to_column() %>%
    # make leaf split points to NA, so the 0s won't get plotted
    mutate(`split point` = ifelse(is.na(prediction), `split point`, NA))
  
  # prepare data frame for graph
  graph_frame <- data.frame(from = rep(tree$rowname, 2),
                            to = c(tree$`left daughter`, tree$`right daughter`))
  
  # convert to graph and delete the last node that we don't want to plot
  graph <- graph_from_data_frame(graph_frame) %>%
    delete_vertices("0")
  
  # set node labels
  V(graph)$node_label <- gsub("_", " ", as.character(tree$`split var`))
  V(graph)$leaf_label <- as.character(tree$prediction)
  V(graph)$split <- as.character(round(tree$`split point`, digits = 2))
  
  # plot
  plot <- ggraph(graph, 'dendrogram') + 
    theme_bw() +
    geom_edge_link() +
    geom_node_point() +
    geom_node_text(aes(label = node_label), na.rm = TRUE, repel = TRUE) +
    geom_node_label(aes(label = split), vjust = 2.5, na.rm = TRUE, fill = "white") +
    geom_node_label(aes(label = leaf_label, fill = leaf_label), na.rm = TRUE, 
                    repel = TRUE, colour = "white", fontface = "bold", show.legend = FALSE) +
    theme(panel.grid.minor = element_blank(),
          panel.grid.major = element_blank(),
          panel.background = element_blank(),
          plot.background = element_rect(fill = "white"),
          panel.border = element_blank(),
          axis.line = element_blank(),
          axis.text.x = element_blank(),
          axis.text.y = element_blank(),
          axis.ticks = element_blank(),
          axis.title.x = element_blank(),
          axis.title.y = element_blank(),
          plot.title = element_text(size = 18))
  
  print(plot)
}
tree_func(fmodel, 1)
## Warning: Duplicated aesthetics after name standardisation: na.rm

## Warning: Duplicated aesthetics after name standardisation: na.rm

## Warning: Duplicated aesthetics after name standardisation: na.rm

## Warning: Removed 50 rows containing missing values (geom_text_repel).

## Warning: Removed 50 rows containing missing values (geom_label).

## Warning: Removed 49 rows containing missing values (geom_label_repel).