Select Language

AI社区

公开数据集

四足哺乳动物数据集

四足哺乳动物数据集

4K
363 浏览
0 喜欢
0 次下载
0 条讨论
Life Classification

Data Set Information:The file animals.c is a data generator of structured instances representing quadruped animals as us......

数据结构 ? 4K

    Data Structure ?

    * 以上分析是由系统提取分析形成的结果,具体实际数据为准。

    README.md


    Data Set Information:

    The file animals.c is a data generator of structured instances representing quadruped animals as used by Gennari, Langley, and Fisher (1989) to evaluate the CLASSIT unsupervised learning algorithm. Instances have 8 components: neck, four legs, torso, head, and tail.  Each component is represented as a simplified/generalized cylinder (i.e., inspired by David Marr's work in "Vision: A Computational Investigation Into the Human Representation  and Processing of Visual Information", published by Freeman in 1982). Each cylinder is itself described by 9 attributes: location x 3, axis x 3, height, radius, and texture.  This code generates instances in one of four classes: dogs, cats, horses, and giraffes.  The program generates instances by selecting a class according to a distribution determined by function rand4().  Each class has a prototype; the prototype of the selected class is perturbed according to a distribution described in the code for the four classes (i.e., parameterized means with Guassian distributions are used to represent prototypes and perturbation distributions, where the means are used to distinguish the four classes).

    From John Gennari: (1990)

    The only notes I have about it is that I don't use the data format it creates any more. To change this, modify "printpart()". Also, it uses a very rough approximation for a bell-shaped distribution. Currently, I use a much more sophisticated random number generator. To fix this, just replace "bellrand()" with a real bell shaped distribution.


    Attribute Information:

    A. Eight components per instances/animal:
           1. Head
           2. Tail
           3. 4 legs
           4. torso
           5. neck  
        B. Nine attributes per component:
           1. Location 1
           2. Location 2
    3. Location 3
    4. Axis 1
    5. Axis 2
    6. Axis 3
    7. Height
    8. Radius
    9. Texture


    Relevant Papers:

    N/A



    Citation Request:

    Please refer to the Machine Learning Repository's citation policy


    Origin:

    Gennari, J.~H., Langley, P, & Fisher, D. (1989).
    Models of incremental concept formation. {it Artificial Intelligence/}, {it 40/}, 11--61.

    Donor:

    John H. Gennari (gennari '@' camis.stanford.edu 8/1992)




    ×

    帕依提提提温馨提示

    该数据集正在整理中,为您准备了其他渠道,请您使用

    注:部分数据正在处理中,未能直接提供下载,还请大家理解和支持。
    暂无相关内容。
    暂无相关内容。
    • 分享你的想法
    去分享你的想法~~

    全部内容

      欢迎交流分享
      开始分享您的观点和意见,和大家一起交流分享.
    所需积分:3 去赚积分?
    • 363浏览
    • 0下载
    • 0点赞
    • 收藏
    • 分享