USCongress: a sample dataset containing labeled bills from the United...

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

Description

A sample dataset containing labeled bills from the United States Congress, compiled by Professor John D. Wilkerson at the University of Washington, Seattle and E. Scott Adler at the University of Colorado, Boulder.

Usage

data(USCongress)

Format

A data.frame containing five columns.

1. ID - A unique identifier for the bill.

2. cong - The session of congress that the bill first appeared in.

3. billnum - The number of the bill as it appears in the congressional docket.

4. h_or_sen - A field specifying whether the bill was introduced in the House (HR) or the Senate (S).

5. major - A manually labeled topic code corresponding to the subject of the bill.

Source

http://www.congressionalbills.org/

Examples

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

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.