In IndrajeetPatil/mlvizstats:

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  out.width = "100%"
)

# needed libraries
library(randomForest)
library(magrittr)

Deciding on how to split tree

Input <- ("
Week Sky_condition Wind_speed Humidity Result
1 cloudy low high yes
2 rainy low normal yes
3 sunny high normal yes
4 cloudy high high yes
5 cloudy low normal yes
6 rainy high high no
7 rainy high normal no
8 cloudy high normal yes
9 sunny low high no
10 sunny low normal yes
11 rainy low normal yes
12 sunny low high no
13 sunny high high no
")

# creating a dataframe
(cycling <- read.table(textConnection(Input), header = TRUE) %>%
  tibble::as_tibble(.))

Checking fits

# fitting model
fit <- randomForest::randomForest(formula = factor(Result) ~ ., 
                                  data = cycling[2:5], 
                                  ntree = 1000)

# summary
fit

# Sky_condition has the highest gain?
randomForest::varImpPlot(fit)

IndrajeetPatil/mlvizstats documentation built on May 30, 2019, 4:01 a.m.