A classic mushroom dataset from the UCI Machine Learning Repository, containing 8,124 samples and 22 classification features, used to determine whether mushrooms are edible or poisonous, is a standard introductory dataset for classification learning.
Pure classification feature dataset, suitable for learning decision trees and rule mining
Determine whether a mushroom is edible or poisonous, with intuitive and practical results.
All 22 features are categorical variables (cap shape, color, odor, etc.), suitable for practicing one-hot encoding and label encoding.
Categorical features make it an ideal dataset for learning decision trees, random forests, and rule learning algorithms.
8,124 samples are sufficient, with a relatively balanced distribution of edible and poisonous categories.
Single features like odor can achieve nearly perfect classification, suitable for exploring feature importance.
Originating from the UCI Machine Learning Repository, a classic binary classification dataset widely cited in academia.
From beginner learning to advanced feature analysis, it can provide value
Pure classification features are very suitable for learning decision trees, CART, and rule learning algorithms
Using algorithms such as Naive Bayes, logistic regression, SVM for edible/poisonous classification
Discover the strong predictive power of key features like odor, practice information gain and chi-squared tests
Practice techniques for one-hot encoding, label encoding, and target encoding of categorical variables
The following are examples of the first few rows of the mushroom dataset (all features are encoded with single-letter codes)
class,cap_shape,cap_surface,cap_color,bruises,odor,gill_attachment,...,habitat p,x,s,n,t,p,f,c,n,k,e,e,s,s,w,w,p,w,o,p,k,s,u e,x,s,y,t,a,f,c,b,k,e,c,s,s,w,w,p,w,o,p,n,n,g e,b,s,w,t,l,f,c,b,n,e,c,s,s,w,w,p,w,o,p,n,n,m p,x,y,w,t,p,f,c,n,n,e,e,s,s,w,w,p,w,o,p,k,s,u e,x,s,g,f,n,f,w,b,k,t,e,s,s,w,w,p,w,o,e,n,a,g
From browsing to analysis, you can start your data science project in just a few minutes
View dataset details on the Ace Data Cloud platform, including field descriptions, sample size, and licensing agreements.
Download the CSV file (374 KB), data is ready to use without additional cleaning.
Use pandas.read_csv() to load the data, along with pd.get_dummies() to encode categorical features.
A classic classification dataset with open licensing, available for immediate download. The purely categorical feature design makes it an ideal introductory dataset for decision trees and rule learning.
