March 2019
Beginner to intermediate
448 pages
13h 14m
English
Content preview from R Statistics Cookbook
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How to do it...
This dataset has 8,124 samples of mushrooms that can be either poisonous or edible; the objective is to predict which ones are edible or poisonous based on 22 categorical features that relate to the physical characteristics of each mushroom.
We will show different ways of partitioning this dataset using several caret tools:
- First, we load the caret library and the mushroom dataset. This dataset does not contain the column names, so we need to add them after loading the data:
library(caret)mushroom_data = read.csv("https://archive.ics.uci.edu/ml/machine-learning-databases/mushroom/agaricus-lepiota.data",head=FALSE)colnames(mushroom_data) = c("edible","cap-shape", "cap-surface", "cap-color","bruises","odor", "gill-attachment","gill-spacing","gill-size","gill-color","stalk-shape", ...
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