iris

鸢尾花数据集是英国统计学家和生物学家 Ronald Fisher 在其 1936 年的论文 The use of multiple measurement in taxonomic questions 中引入的多元数据集。它有时被称为安德森鸢尾花数据集，因为埃德加安德森收集数据以量化三种相关物种鸢尾花的形态变异。该数据集包含来自三种鸢尾花（鸢尾花、维吉尼亚鸢尾和杂色鸢尾）中的每种鸢尾花的 50 个样本。从每个样本中测量了四个特征：萼片和花瓣的长度和宽度，以厘米为单位。该数据集成为机器学习中许多统计分类技术（如支持向量机）的典型测试用例The Iris flower dataset is a multivariate dataset introduced by British statistician and biologist Ronald Fisher in his 1936 paper *The use of multiple measurements in taxonomic questions*. It is sometimes referred to as Anderson's Iris dataset, as Edgar Anderson collected the data to quantify the morphological variation among three related Iris species. This dataset contains 50 samples from each of three Iris species: Iris setosa, Iris virginica, and Iris versicolor. Four features were measured from each sample: the length and the width of both sepals and petals, in centimeters. This dataset has become a canonical test case for many statistical classification techniques in machine learning, such as Support Vector Machines.

搜集汇总

背景与挑战

背景概述

鸢尾花数据集是Ronald Fisher于1936年提出的经典多元数据集，包含三种鸢尾花物种各50个样本，每个样本测量了萼片和花瓣的长度与宽度四个特征，常用于机器学习分类算法的测试。该数据集由筑波大学于2020年发布。