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#' Data set Thyroid Disease (thyroid0387)
#'
#' This data set if one of the several databases about Thyroid avalaible at the UCI repository.
#' The task is to detect is a given patient is normal (1) or suffers from hyperthyroidism (2)
#' or hypothyroidism (3) .
#'
#' \describe{
#' \item{Age}{Age of the patient (0.01--0.97). Continuous variable.}
#' \item{Sex}{Sex of the patient, 0 (Male) 1 (Female). Binary variable. }
#' \item{On_thyroxine}{0 (FALSE) 1 (TRUE). Binary variable.}
#' \item{Query_on_thyroxine}{0 (FALSE) 1 (TRUE). Binary variable.}
#' \item{On_antithyroid_medication}{0 (FALSE) 1 (TRUE). Binary variable.}
#' \item{Sick}{0 (FALSE) 1 (TRUE). Binary variable.}
#' \item{Pregnant}{0 (FALSE) 1 (TRUE). Binary variable.}
#' \item{Thyroid_surgery}{0 (FALSE) 1 (TRUE). Binary variable.}
#' \item{I131_treatment}{0 (FALSE) 1 (TRUE). Binary variable.}
#' \item{Query_hypothyroid}{0 (FALSE) 1 (TRUE). Binary variable.}
#' \item{Query_hyperthyroid}{0 (FALSE) 1 (TRUE). Binary variable.}
#' \item{Lithium}{0 (FALSE) 1 (TRUE). Binary variable.}
#' \item{Goitre}{0 (FALSE) 1 (TRUE). Binary variable.}
#' \item{Tumor}{0 (FALSE) 1 (TRUE). Binary variable.}
#' \item{Hypopituitary}{0 (FALSE) 1 (TRUE). Binary variable.}
#' \item{Psych}{0 (FALSE) 1 (TRUE). Binary variable.}
#' \item{TSH}{amount of TSH (0.0--0.53). Continuous variable.}
#' \item{T3}{amount of T3 (0.0005--0.18). Continuous variable.}
#' \item{TT4}{amount of TT4 (0.002--0.6). Continuous variable.}
#' \item{T4U}{amount of T4U (0.017--0.233). Continuous variable.}
#' \item{FTI}{amount of FTI (0.002--0.642). Continuous variable.}
#' \item{Class}{1 (normal) 2 (hyperthyroidism) 3 (hypothyroidism). Class variable.}
#' }
#' @format A data frame with 7200 rows, 21 variables and the class.
#' @source \url{http://archive.ics.uci.edu/ml/datasets/Thyroid+Disease}
#' @name thyroid
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#' Data set Ecoli: Protein Localization Sites
#'
#' This data set contains information of Escherichia coli. It is a
#' bacterium of the genus Escherichia that is commonly found in the
#' lower intestine of warm-blooded organism.
#'
#' \describe{
#' \item{Sequence Name}{Accession number for the SWISS-PROT database.}
#' \item{mcg}{McGeoch's method for signal sequence recognition.}
#' \item{gvh}{Von Heijne's method for signal sequence recognition.}
#' \item{lip}{Von Heijne's Signal Peptidase II consensus sequence score. Binary attribute.}
#' \item{chg}{Presence of charge on N-terminus of predicted lipoproteins. Binary attribute.}
#' \item{aac}{Score of discriminant analysis of the amino acid content of outer membrane and periplasmic proteins.}
#' \item{alm1}{Score of the ALOM membrane spanning region prediction program.}
#' \item{alm2}{Score of ALOM program after excluding putative cleavable signal regions from the sequence.}
#' \item{Class}{Class variable. 8 possibles states.}
#' }
#' @format A data frame with 336 rows, 8 variables and the class.
#' @source \url{http://archive.ics.uci.edu/ml/datasets/Ecoli}
#' @name ecoli
NULL
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