Mushroom Classification（蘑菇分类数据集）

Mushroom Classification（蘑菇分类数据集）

原文：

Mushroom Classification

Safe to eat or deadly poison?

Although this dataset was originally contributed to the UCI Machine Learning repository nearly 30 years ago, mushroom hunting (otherwise known as "shrooming") is enjoying new peaks in popularity. Learn which features spell certain death and which are most palatable in this dataset of mushroom characteristics. And how certain can your model be?

This dataset includes descriptions of hypothetical samples corresponding to 23 species of gilled mushrooms in the Agaricus and Lepiota Family Mushroom drawn from The Audubon Society Field Guide to North American Mushrooms (1981). Each species is identified as definitely edible, definitely poisonous, or of unknown edibility and not recommended. This latter class was combined with the poisonous one. The Guide clearly states that there is no simple rule for determining the edibility of a mushroom; no rule like "leaflets three, let it be'' for Poisonous Oak and Ivy.

Time period: Donated to UCI ML 27 April 1987

Inspiration

What types of machine learning models perform best on this dataset?Which features are most indicative of a poisonous mushroom?

译：

蘑菇分类

安全食用还是致命毒药？

尽管这个数据集最初是在近30年前提供给UCI机器学习库的，但蘑菇搜索（也称为“shrooming”）正迎来新的流行高峰。了解哪些特征会导致死亡，哪些特征在蘑菇特征数据集中最容易被接受。你的模型有多确定？

该数据集包括根据奥杜邦协会北美蘑菇实地指南（1981年）得出的蘑菇和麻风菌科23种有鳃蘑菇的假设样本的描述。每一种都被确定为绝对可食用，绝对有毒，或未知食用性，不推荐。后一类是和有毒的一类结合在一起的。该指南明确指出，没有简单的规则来确定蘑菇的可食性；对于有毒的橡树和常春藤来说，没有“传单三，随它去吧”这样的规则。

●时间：1987年4月27日捐赠给UCI ML

灵感

●什么类型的机器学习模型在这个数据集中表现最好？

●哪些特征最能说明有毒蘑菇？

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