Source:

David Gil,
dgil '@' dtic.ua.es,
Lucentia Research Group, Department of Computer Technology, University of Alicante

Jose Luis Girela,
girela '@' ua.es,
Department of Biotechnology, University of Alicante

Data Set Information:

Provide all relevant information about your data set.

Attribute Information:

Season in which the analysis was performed. 1) winter, 2) spring, 3) Summer, 4) fall. (-1, -0.33, 0.33, 1)

Age at the time of analysis. 18-36 (0, 1)

Childish diseases (ie , chicken pox, measles, mumps, polio) 1) yes, 2) no. (0, 1)

Accident or serious trauma 1) yes, 2) no. (0, 1)

Surgical intervention 1) yes, 2) no. (0, 1)

High fevers in the last year 1) less than three months ago, 2) more than three months ago, 3) no. (-1, 0, 1)

Frequency of alcohol consumption 1) several times a day, 2) every day, 3) several times a week, 4) once a week, 5) hardly ever or never (0, 1)

Smoking habit 1) never, 2) occasional 3) daily. (-1, 0, 1)

Number of hours spent sitting per day ene-16 (0, 1)

Output: Diagnosis normal (N), altered (O)

Relevant Papers:

David Gil, Jose Luis Girela, Joaquin De Juan, M. Jose Gomez-Torres, and
Magnus Johnsson. Predicting seminal quality with artificial intelligence
methods. Expert Systems with Applications, 39(16):12564 – 12573, 2012

Citation Request:

David Gil, Jose Luis Girela, Joaquin De Juan, M. Jose Gomez-Torres, and
Magnus Johnsson. Predicting seminal quality with artificial intelligence
methods. Expert Systems with Applications, 39(16):12564 – 12573, 2012

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