NYTimes: a sample dataset containing labeled headlines from The New...

In maxent: Low-memory Multinomial Logistic Regression with Support for Text Classification

Description

A sample dataset containing labeled headlines from The New York Times, compiled by Professor Amber E. Boydstun at the University of California, Davis.

Usage

data(NYTimes)

Format

A data.frame containing five columns.

1. Article_ID - A unique identifier for the headline from The New York Times.

2. Date - The date the headline appeared in The New York Times.

3. Title - The headline as it appeared in The New York Times.

4. Subject - A manually classified subject of the headline.

5. Topic.Code - A manually labeled topic code corresponding to the subject.

Source

http://www.amberboydstun.com/

Examples

# READ THE CSV
data <- read.csv(system.file("data/NYTimes.csv.gz",package="maxent"))
# ALTERNATIVELY, USE THE data() FUNCTION
data(NYTimes)

Example output

Loading required package: SparseM

Attaching package: 'SparseM'

The following object is masked from 'package:base':

    backsolve

Loading required package: tm
Loading required package: NLP
Warning message:
In scan(file = file, what = what, sep = sep, quote = quote, dec = dec,  :
  EOF within quoted string

maxent documentation built on May 29, 2017, 1:40 p.m.