Spam: Spam Example Dataset

In ExactSampling: ExactSampling: risk evaluation using exact resampling methods for the k Nearest Neighbor algorithm.

Description

The spam dataset is available and fully described on the UCI spambase directory, and has been used for instance in Hastie et al. (2001). The dataset is a collection of 4601 spam and non-spam e-mails, described by 57 continuous variables (and the nominal class label).

Usage

data(Spam)

Details

A data frame with 4601 observations on the following 58 variables:

• [,1:57] numeric Descriptors of the email contents, mostly word or character appearance percentage. See the UCI spambase directory for more information.

• [,58] factor Labels: regular (0) or spam (1) email.

Source

UCI spambase directory :
ftp://ftp.ics.uci.edu/pub/machine-learning-databases/spambase/

References

Hastie, T. Tibshirani, R. and Friedman, J. (2001) Chapter 9 of The Elements of Statistical Learning: Data Mining, Inference, and Prediction, eds Springer, New York

Examples

data(Spam)

ExactSampling documentation built on May 2, 2019, 6:08 p.m.