Author: Professor Jergen at Baylor College of Medicine
Source: [UCI](https://archive.ics.uci.edu/ml/datasets/Audiology+(Standardized))
Please cite: Bareiss, E. Ray, & Porter, Bruce (1987). Protos: An Exemplar-Based Learning Apprentice. In the Proceedings of the 4th International Workshop on Machine Learning, 12-23, Irvine, CA: Morgan Kaufmann
Audiology Database
This database is a standardized version of the original audiology database (see audiology.* in this directory). The non-standard set of attributes have been converted to a standard set of attributes according to the rules that follow.
* Each property that appears anywhere in the original .data or .test file has been represented as a separate attribute in this file.
* A property such as age_gt_60 is represented as a boolean attribute with values f and t.
* In most cases, a property of the form x(y) is represented as a discrete attribute x() whose possible values are the various y's; air() is an example. There are two exceptions:
when only one value of y appears anywhere, e.g. static(normal). In this case, x_y appears as a boolean attribute.
when one case can have two or more values of x, e.g. history(..). All possible values of history are treated as separate boolean attributes.
* Since boolean attributes only appear as positive conditions, each boolean attribute is assumed to be false unless noted as true. The value of multi-value discrete attributes taken as unknown ("?") unless a value is specified.
* The original case identifications, p1 to p200 in the .data file and t1 to t26 in the .test file, have been added as a unique identifier attribute.
[Note: in the original .data file, p165 has a repeated specification of o_ar_c(normal); p166 has repeated specification of speech(normal) and conflicting values air(moderate) and air(mild). No other problems with the original data were noted.]
### Attribute Information:
age_gt_60: f, t.
air(): mild,moderate,severe,normal,profound.
airBoneGap: f, t.
ar_c(): normal,elevated,absent.
ar_u(): normal,absent,elevated.
bone(): mild,moderate,normal,unmeasured.
boneAbnormal: f, t.
bser(): normal,degraded.
history_buzzing: f, t.
history_dizziness: f, t.
history_fluctuating: f, t.
history_fullness: f, t.
history_heredity: f, t.
history_nausea: f, t.
history_noise: f, t.
history_recruitment: f, t.
history_ringing: f, t.
history_roaring: f, t.
history_vomiting: f, t.
late_wave_poor: f, t.
m_at_2k: f, t.
m_cond_lt_1k: f, t.
m_gt_1k: f, t.
m_m_gt_2k: f, t.
m_m_sn: f, t.
m_m_sn_gt_1k: f, t.
m_m_sn_gt_2k: f, t.
m_m_sn_gt_500: f, t.
m_p_sn_gt_2k: f, t.
m_s_gt_500: f, t.
m_s_sn: f, t.
m_s_sn_gt_1k: f, t.
m_s_sn_gt_2k: f, t.
m_s_sn_gt_3k: f, t.
m_s_sn_gt_4k: f, t.
m_sn_2_3k: f, t.
m_sn_gt_1k: f, t.
m_sn_gt_2k: f, t.
m_sn_gt_3k: f, t.
m_sn_gt_4k: f, t.
m_sn_gt_500: f, t.
m_sn_gt_6k: f, t.
m_sn_lt_1k: f, t.
m_sn_lt_2k: f, t.
m_sn_lt_3k: f, t.
middle_wave_poor: f, t.
mod_gt_4k: f, t.
mod_mixed: f, t.
mod_s_mixed: f, t.
mod_s_sn_gt_500: f, t.
mod_sn: f, t.
mod_sn_gt_1k: f, t.
mod_sn_gt_2k: f, t.
mod_sn_gt_3k: f, t.
mod_sn_gt_4k: f, t.
mod_sn_gt_500: f, t.
notch_4k: f, t.
notch_at_4k: f, t.
o_ar_c(): normal,elevated,absent.
o_ar_u(): normal,absent,elevated.
s_sn_gt_1k: f, t.
s_sn_gt_2k: f, t.
s_sn_gt_4k: f, t.
speech(): normal,good,very_good,very_poor,poor,unmeasured.
static_normal: f, t.
tymp(): a,as,b,ad,c.
viith_nerve_signs: f, t.
wave_V_delayed: f, t.
waveform_ItoV_prolonged: f, t.
indentifier (unique for each instance)
class:
cochlear_unknown,mixed_cochlear_age_fixation,poss_central
mixed_cochlear_age_otitis_media,mixed_poss_noise_om,
cochlear_age,normal_ear,cochlear_poss_noise,cochlear_age_and_noise,
acoustic_neuroma,mixed_cochlear_unk_ser_om,conductive_discontinuity,
retrocochlear_unknown,conductive_fixation,bells_palsy,
cochlear_noise_and_heredity,mixed_cochlear_unk_fixation,
otitis_media,possible_menieres,possible_brainstem_disorder,
cochlear_age_plus_poss_menieres,mixed_cochlear_age_s_om,
mixed_cochlear_unk_discontinuity,mixed_poss_central_om