原文：

Abalone Data Set

Predict the age of abalone from physical measurements

Data Set Information:

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.

From the original data examples with missing values were removed (the majority having the predicted value missing), and the ranges of the continuous values have been scaled for use with an ANN (by dividing by 200).

Attribute Information:

Given is the attribute name, attribute type, the measurement unit and a brief description. The number of rings is the value to predict: either as a continuous value or as a classification problem.

Name / Data Type / Measurement Unit / Description

-----------------------------

Sex / nominal / -- / M, F, and I (infant)

Length / continuous / mm / Longest shell measurement

Diameter / continuous / mm / perpendicular to length

Height / continuous / mm / with meat in shell

Whole weight / continuous / grams / whole abalone

Shucked weight / continuous / grams / weight of meat

Viscera weight / continuous / grams / gut weight (after bleeding)

Shell weight / continuous / grams / after being dried

Rings / integer / -- / +1.5 gives the age in years

The readme file contains attribute statistics.

译：

鲍鱼数据集

通过物理测量预测鲍鱼的年龄

据集信息：

通过物理测量预测鲍鱼的年龄。鲍鱼的年龄是通过将壳切开，染色，并通过显微镜计数环的数量来确定的——这是一项既枯燥又耗时的任务。其他更容易获得的测量值用于预测年龄。可能需要进一步的信息，如天气模式和位置（因此食物可用性）来解决问题。

从原始数据中，删除了缺失值的示例（大多数具有缺失的预测值），并缩放了连续值的范围，以便与ANN一起使用（除以200）。

属性信息：

给出了属性名称、属性类型、测量单位和简要说明。环的数量是要预测的值：要么作为连续值，要么作为分类问题。

名称/数据类型/测量单位/说明

-----------------------------

性别/标称/--/M、F和I（婴儿）

长度/连续/毫米/最长外壳测量

直径/连续/毫米/垂直于长度

高度/连续/毫米/带壳肉

全重/连续/克/整条鲍鱼

去皮重量/连续/克/肉重量

内脏重量/连续/克/肠道重量（出血后）

壳重/连续/克/干燥后

Rings/integer/--/+1.5给出了以年为单位的年龄

自述文件包含属性统计信息。

数据示例：

M,0.455,0.365,0.095,0.514,0.2245,0.101,0.15,15
M,0.35,0.265,0.09,0.2255,0.0995,0.0485,0.07,7
F,0.53,0.42,0.135,0.677,0.2565,0.1415,0.21,9
M,0.44,0.365,0.125,0.516,0.2155,0.114,0.155,10
I,0.33,0.255,0.08,0.205,0.0895,0.0395,0.055,7
I,0.425,0.3,0.095,0.3515,0.141,0.0775,0.12,8
F,0.53,0.415,0.15,0.7775,0.237,0.1415,0.33,20
F,0.545,0.425,0.125,0.768,0.294,0.1495,0.26,16
M,0.475,0.37,0.125,0.5095,0.2165,0.1125,0.165,9
F,0.55,0.44,0.15,0.8945,0.3145,0.151,0.32,19
F,0.525,0.38,0.14,0.6065,0.194,0.1475,0.21,14
M,0.43,0.35,0.11,0.406,0.1675,0.081,0.135,10
M,0.49,0.38,0.135,0.5415,0.2175,0.095,0.19,11
F,0.535,0.405,0.145,0.6845,0.2725,0.171,0.205,10
F,0.47,0.355,0.1,0.4755,0.1675,0.0805,0.185,10
M,0.5,0.4,0.13,0.6645,0.258,0.133,0.24,12
I,0.355,0.28,0.085,0.2905,0.095,0.0395,0.115,7
F,0.44,0.34,0.1,0.451,0.188,0.087,0.13,10
M,0.365,0.295,0.08,0.2555,0.097,0.043,0.1,7
M,0.45,0.32,0.1,0.381,0.1705,0.075,0.115,9
M,0.355,0.28,0.095,0.2455,0.0955,0.062,0.075,11
I,0.38,0.275,0.1,0.2255,0.08,0.049,0.085,10
F,0.565,0.44,0.155,0.9395,0.4275,0.214,0.27,12
F,0.55,0.415,0.135,0.7635,0.318,0.21,0.2,9
F,0.615,0.48,0.165,1.1615,0.513,0.301,0.305,10
F,0.56,0.44,0.14,0.9285,0.3825,0.188,0.3,11
F,0.58,0.45,0.185,0.9955,0.3945,0.272,0.285,11
M,0.59,0.445,0.14,0.931,0.356,0.234,0.28,12
M,0.605,0.475,0.18,0.9365,0.394,0.219,0.295,15
M,0.575,0.425,0.14,0.8635,0.393,0.227,0.2,11