abalone: Abalone Data Set

In coatless/ucidata: Collection of Datasets from the UC Irvine Machine Learning Repository

Abalone Data Set

Description

Predicting the age of abalone from physical measurements. The age of abalone is determined by cutting the shell through the cone, staining it, and counting the number of rings through a microscope – a boring and time-consuming task. Other measurements, which are easier to obtain, are used to predict the age. Further information, such as weather patterns and location (hence food availability) may be required to solve the problem.

Usage

abalone

Format

A data frame with 4177 observations on the following 9 variables.

• sex: Factor

  • M (Male), F (Female), and I (Infant)

• length: Numeric

  • Longest shell measurement (mm)

• diameter: Numeric

  • Perpendicular to length (mm)

• height: Numeric

  • With meat in shell (mm)

• whole_weight: Numeric

  • Whole abalone weight (grams)

• shucked_weight: Numeric

  • Weight of meat (grams)

• viscera_weight: Numeric

  • Gut weight after bleeding (grams)

• shell_weight: Numeric

  • Shell weight after being dried (grams)

• rings: Integer

  • Adding 1.5 gives the age in years

Source

Marine Resources Division Marine Research Laboratories - Taroona Department of Primary Industry and Fisheries, Tasmania GPO Box 619F, Hobart, Tasmania 7001, Australia (contact: Warwick Nash [phone], wnash '@' dpi.tas.gov.au)

References

Warwick J Nash, Tracy L Sellers, Simon R Talbot, Andrew J Cawthorn and Wes B Ford (1994) "The Population Biology of Abalone (Haliotis species) in Tasmania. I. Blacklip Abalone (H. rubra) from the North Coast and Islands of Bass Strait", Sea Fisheries Division, Technical Report No. 48 (ISSN 1034-3288)

https://archive.ics.uci.edu/ml/machine-learning-databases/abalone/

https://archive.ics.uci.edu/ml/datasets/abalone

coatless/ucidata documentation built on Nov. 17, 2023, 9:19 a.m.