HouseVotes84             package:mlbench             R Documentation

_U_n_i_t_e_d _S_t_a_t_e_s _C_o_n_g_r_e_s_s_i_o_n_a_l _V_o_t_i_n_g _R_e_c_o_r_d_s _1_9_8_4

_D_e_s_c_r_i_p_t_i_o_n:

     This data set includes votes for each of the U.S. House of
     Representatives Congressmen on the 16 key votes identified by the
     CQA.  The CQA lists nine different types of votes: voted for,
     paired for, and announced for (these three simplified to yea),
     voted against, paired against, and announced against (these three
     simplified to nay), voted present, voted present to avoid conflict
     of interest, and did not vote or otherwise make a position known
     (these three simplified to an unknown disposition).

_U_s_a_g_e:

     data(HouseVotes84)

_F_o_r_m_a_t:

     A data frame with 435 observations on 17 variables:

        1  Class Name: 2 (democrat, republican)
        2  handicapped-infants: 2 (y,n)
        3  water-project-cost-sharing: 2 (y,n)
        4  adoption-of-the-budget-resolution: 2 (y,n)
        5  physician-fee-freeze: 2 (y,n)
        6  el-salvador-aid: 2 (y,n)
        7  religious-groups-in-schools: 2 (y,n)
        8  anti-satellite-test-ban: 2 (y,n)
        9  aid-to-nicaraguan-contras: 2 (y,n)
       10  mx-missile: 2 (y,n)
       11  immigration: 2 (y,n)
       12  synfuels-corporation-cutback: 2 (y,n)
       13  education-spending: 2 (y,n)
       14  superfund-right-to-sue: 2 (y,n)
       15  crime: 2 (y,n)
       16  duty-free-exports: 2 (y,n)
       17  export-administration-act-south-africa: 2 (y,n)

_S_o_u_r_c_e:

        *  Source: Congressional Quarterly Almanac, 98th Congress, 2nd
           session 1984, Volume XL: Congressional Quarterly Inc.,
           ington, D.C., 1985

        *  Donor: Jeff Schlimmer (Jeffrey.Schlimmer@a.gp.cs.cmu.edu)

     These data have been taken from the UCI Repository Of Machine
     Learning Databases at

        *  <URL: ftp://ftp.ics.uci.edu/pub/machine-learning-databases>

        *  <URL: http://www.ics.uci.edu/~mlearn/MLRepository.html>

     and were converted to R format by
     Friedrich.Leisch@ci.tuwien.ac.at.

