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  • weka基础数据集

    2018-10-01 01:58:03
    weka自带数据集,数据挖掘基础需要用到的,可以在weka根目录的data中找到
  • weka软件最全数据集

    2019-04-12 17:10:48
    weka软件最全数据集,共189个,用于weka软件的数据集训练和测试,包含天气 车辆 肝脏肿瘤等等数据集,格式为arff
  • weka经典七个数据集

    2016-04-19 19:38:34
    weka 数据挖掘 bank_data.arff wine.arff等
  • weka安装自带数据集

    2011-01-20 17:50:23
    weka安装自带数据集,安装weka后在weka根目录下的data文件夹下可以找到。
  • Mac版本Weka自带数据集在哪里

    千次阅读 2020-04-02 11:08:31
    Mac下载Weka后,自带的数据集在哪里 首先下载好Weka,下好后发现不像... weka.jar 找到包含自带数据集的压缩包,并进行压缩。 压缩后,就可以直接搜索你要的数据集了,比如说我在第一次实验中要用到的iris.ar...

    Mac下载Weka后,自带的数据集在哪里

    首先下载好Weka,下好后发现不像windows一样,找不到自带的数据集。不过后来在一个压缩包里面找到了它。

    数据集位置

    首先显示weka的包内容
    打开weka包
    然后通过路径Contents -> Java -> weka.jar 找到包含自带数据集的压缩包,并进行压缩。

    压缩包位置
    复制到外面压缩,压缩后,就可以直接搜索你要的数据集了,比如说我在第一次实验中要用到的iris.arff位置在weka -> gui -> beans -> templates -> iris.arff。

    iris.arff位置
    总感觉好像有别的操作方式,希望有大神能路过给予指点👏
    作为小白的Mac用户,在学习计算机的过程中总是遇到一些奇奇怪怪的问题(可能问题太简单,只有小白才会问,总是不能在某度找到答案)。这次我打算记录下来,方便自己以后查看,也希望可以帮助和我一样小白的同学~

    展开全文
  • weka数据集学习

    2021-02-22 20:05:27
    每次先选定数据集,才可以继续选择上方的分类、聚类等 ...Weka处理的数据集通常是存放在一种叫ARFF格式的文件中的。那么,什么是ARFF呢? 以weather.nominal.arff数据集为例,完整的数据集如下表示:.

     每次先选定数据集,才可以继续选择上方的分类、聚类等

    观察数据集weather.nominal.arff

    weather.numeric.arff

    观察上面两组天气数据,区别在温度和湿度,离散的连续的

    温度取最小值,最大值、平均值和标准差,湿度类似

    玻璃数据集glass.arff

    Weka数据集格式-ARFF

    Weka处理的数据集通常是存放在一种叫ARFF格式的文件中的。那么,什么是ARFF呢?

    以weather.nominal.arff数据集为例,完整的数据集如下表示:

    @relation weather.symbolic
    
    @attribute outlook {sunny, overcast, rainy}
    @attribute temperature {hot, mild, cool}
    @attribute humidity {high, normal}
    @attribute windy {TRUE, FALSE}
    @attribute play {yes, no}
    
    @data
    sunny,hot,high,FALSE,no
    sunny,hot,high,TRUE,no
    overcast,hot,high,FALSE,yes
    rainy,mild,high,FALSE,yes
    rainy,cool,normal,FALSE,yes
    rainy,cool,normal,TRUE,no
    overcast,cool,normal,TRUE,yes
    sunny,mild,high,FALSE,no
    sunny,cool,normal,FALSE,yes
    rainy,mild,normal,FALSE,yes
    sunny,mild,normal,TRUE,yes
    overcast,mild,high,TRUE,yes
    overcast,hot,normal,FALSE,yes
    rainy,mild,high,TRUE,no
    

    ARFF定义

    ARFF全称是Attribute-Relation File Format属性关系文件格式。ARFF文件是一种描述了一系列具有相同属性的实例的ASCII文本文件。

    具体一点来说,就是数据集主要是有两部分组成,一部分是属性描述,一部分是数据

    属性描述的这一部分也叫头信息,一般是放在数据集开始,而数据部分叫数据信息,一般是跟在头信息的后面。

    ARFF头信息

    ARFF的头信息包含这个关系的名称,还有一系列属性以及它们的数据类型。

    以weather.nominal.arff数据集为例,标准的数据集的头信息如下表示:

    @relation weather.symbolic
    
    @attribute outlook {sunny, overcast, rainy}
    @attribute temperature {hot, mild, cool}
    @attribute humidity {high, normal}
    @attribute windy {TRUE, FALSE}
    @attribute play {yes, no}

    %开头的句子是ARFF文件的注释。

    在ARFF文件中,注释通常都是以%开头的。另外@RELATION,@ATTRIBUTE,@DATA都是大小写不敏感的,都可以使用。

    @RELATION声明

    通常来说,@RELATION声明应该是在ARFF文件的第一行出现,前面注释啥的不算哈!

    具体的格式如下:@RELATION <relation-name>,这里<relation-name>是一个字符串,表示这个关系的名称。如果这个字符串包含空格的话一定要记得加上空格,否则识别会出现问题的。另外对于名称也有要求,不要使用'{', '}', ','或者'%’开头,或者是在ASCII表中低于\u0021[!]的字符。

    @ATTRIBUTE声明

    @ATTRIBUTE声明主要是用来指定属性的数据名称和类型,具体的格式如下:@ATTRIBUTE <attribute-name> <data-type>,一般来说,<attribute-name>的要求和上面<relation-name>的要求是一样的,Weka支持的数据格式<data-type>主要有以下几种:

    • numeric
    • integer is treated as numeric
    • real is treated as numeric
    • < nominal-specification >
    • string
    • date [< date-format >]
    • relational for multi-instance data (for future use)

    其它的几个估计大家挺好明白,而< nominal-specification >date估计不太好明白,没关系,我们下面再讲。

    Nominal属性

    所谓的Nominal属性就是后面列举一系列的值,比如{,,…},IRIS数据集的class属性就是这么定义的:@ATTRIBUTE class {Iris-setosa,Iris-versicolor,Iris-virginica}。

    date属性

    date属性的定义比较特殊,因为它还涉及到一个格式的问题,所以我们需要指定相关的格式:@ATTRIBUTE <attribute-name> date [<date-format>]。日期的格式是比较复杂的,比如yyyy-MM-dd或者是MM-dd-yyyy等等,因此需要指定。具体的例子如下:@ATTRIBUTE birthday DATE "yyyy-MM-dd HH:mm:ss"对应的可参考的数据集如下:

    @RELATION Timestamps
     
    @ATTRIBUTE timestamp DATE "yyyy-MM-dd HH:mm:ss"
     
    @DATA 
    "2001-04-03 12:12:12"
    "2001-05-03 12:59:55"
    

    ARFF数据信息

    ARFF的数据信息主要是一系列的以,分隔的数据,并且开头的注解是@DATA,还是以weather.nominal.arff数据集为例,它的标准数据信息如下表示:

    @data
    sunny,hot,high,FALSE,no
    sunny,hot,high,TRUE,no
    overcast,hot,high,FALSE,yes
    rainy,mild,high,FALSE,yes
    rainy,cool,normal,FALSE,yes
    rainy,cool,normal,TRUE,no
    overcast,cool,normal,TRUE,yes
    sunny,mild,high,FALSE,no
    sunny,cool,normal,FALSE,yes
    rainy,mild,normal,FALSE,yes
    sunny,mild,normal,TRUE,yes
    overcast,mild,high,TRUE,yes
    overcast,hot,normal,FALSE,yes
    rainy,mild,high,TRUE,no

    @DATA声明

    ARFF文件的数据部分都是跟在@DATA声明后面的。关于数据部分没有什么过多注意的地方,主要是注意数据缺失的情况,比如

    @DATA
    4.4,?,1.5,?,Iris-setosa
    

    注:
    有时数据中有数据比较稀疏,或者要使用one-hot编码时,可能会采用另一种方法记录数据data,如下图所示:
    在这里插入图片描述
    第一列代表第几个属性(从0开始),第二列代表对应的属性值。如果该属性不在.arff文件中则默认其属性值为0!(注意不是缺失值)

    再一个例子,玻璃数据集

    % 1. Title: Glass Identification Database
    % 
    % 2. Sources:
    %     (a) Creator: B. German
    %         -- Central Research Establishment
    %            Home Office Forensic Science Service
    %            Aldermaston, Reading, Berkshire RG7 4PN
    %     (b) Donor: Vina Spiehler, Ph.D., DABFT
    %                Diagnostic Products Corporation
    %                (213) 776-0180 (ext 3014)
    %     (c) Date: September, 1987
    % 
    % 3. Past Usage:
    %     -- Rule Induction in Forensic Science
    %        -- Ian W. Evett and Ernest J. Spiehler
    %        -- Central Research Establishment
    %           Home Office Forensic Science Service
    %           Aldermaston, Reading, Berkshire RG7 4PN
    %        -- Unknown technical note number (sorry, not listed here)
    %        -- General Results: nearest neighbor held its own with respect to the
    %              rule-based system
    % 
    % 4. Relevant Information:n
    %       Vina conducted a comparison test of her rule-based system, BEAGLE, the
    %       nearest-neighbor algorithm, and discriminant analysis.  BEAGLE is 
    %       a product available through VRS Consulting, Inc.; 4676 Admiralty Way,
    %       Suite 206; Marina Del Ray, CA 90292 (213) 827-7890 and FAX: -3189.
    %       In determining whether the glass was a type of "float" glass or not,
    %       the following results were obtained (# incorrect answers):
    % 
    %              Type of Sample                            Beagle   NN    DA
    %              Windows that were float processed (87)     10      12    21
    %              Windows that were not:            (76)     19      16    22
    % 
    %       The study of classification of types of glass was motivated by 
    %       criminological investigation.  At the scene of the crime, the glass left
    %       can be used as evidence...if it is correctly identified!
    % 
    % 5. Number of Instances: 214
    % 
    % 6. Number of Attributes: 10 (including an Id#) plus the class attribute
    %    -- all attributes are continuously valued
    % 
    % 7. Attribute Information:
    %    1. Id number: 1 to 214
    %    2. RI: refractive index
    %    3. Na: Sodium (unit measurement: weight percent in corresponding oxide, as 
    %                   are attributes 4-10)
    %    4. Mg: Magnesium
    %    5. Al: Aluminum
    %    6. Si: Silicon
    %    7. K: Potassium
    %    8. Ca: Calcium
    %    9. Ba: Barium
    %   10. Fe: Iron
    %   11. Type of glass: (class attribute)
    %       -- 1 building_windows_float_processed
    %       -- 2 building_windows_non_float_processed
    %       -- 3 vehicle_windows_float_processed
    %       -- 4 vehicle_windows_non_float_processed (none in this database)
    %       -- 5 containers
    %       -- 6 tableware
    %       -- 7 headlamps
    % 
    % 8. Missing Attribute Values: None
    % 
    % Summary Statistics:
    % Attribute:   Min     Max      Mean     SD      Correlation with class
    %  2. RI:       1.5112  1.5339   1.5184  0.0030  -0.1642
    %  3. Na:      10.73   17.38    13.4079  0.8166   0.5030
    %  4. Mg:       0       4.49     2.6845  1.4424  -0.7447
    %  5. Al:       0.29    3.5      1.4449  0.4993   0.5988
    %  6. Si:      69.81   75.41    72.6509  0.7745   0.1515
    %  7. K:        0       6.21     0.4971  0.6522  -0.0100
    %  8. Ca:       5.43   16.19     8.9570  1.4232   0.0007
    %  9. Ba:       0       3.15     0.1750  0.4972   0.5751
    % 10. Fe:       0       0.51     0.0570  0.0974  -0.1879
    % 
    % 9. Class Distribution: (out of 214 total instances)
    %     -- 163 Window glass (building windows and vehicle windows)
    %        -- 87 float processed  
    %           -- 70 building windows
    %           -- 17 vehicle windows
    %        -- 76 non-float processed
    %           -- 76 building windows
    %           -- 0 vehicle windows
    %     -- 51 Non-window glass
    %        -- 13 containers
    %        -- 9 tableware
    %        -- 29 headlamps
    % 
    % 
    % 
    %
    %
    %
    %
    % Relabeled values in attribute 'Type'
    %    From: '1'                     To: 'build wind float'    
    %    From: '2'                     To: 'build wind non-float'
    %    From: '3'                     To: 'vehic wind float'    
    %    From: '4'                     To: 'vehic wind non-float'
    %    From: '5'                     To: containers          
    %    From: '6'                     To: tableware           
    %    From: '7'                     To: headlamps           
    %
    @relation Glass
    @attribute 'RI' numeric
    @attribute 'Na' numeric
    @attribute 'Mg' numeric
    @attribute 'Al' numeric
    @attribute 'Si' numeric
    @attribute 'K' numeric
    @attribute 'Ca' numeric
    @attribute 'Ba' numeric
    @attribute 'Fe' numeric
    @attribute 'Type' { 'build wind float', 'build wind non-float', 'vehic wind float', 'vehic wind non-float', containers, tableware, headlamps}
    @data
    1.51793,12.79,3.5,1.12,73.03,0.64,8.77,0,0,'build wind float'
    1.51643,12.16,3.52,1.35,72.89,0.57,8.53,0,0,'vehic wind float'
    1.51793,13.21,3.48,1.41,72.64,0.59,8.43,0,0,'build wind float'
    1.51299,14.4,1.74,1.54,74.55,0,7.59,0,0,tableware
    1.53393,12.3,0,1,70.16,0.12,16.19,0,0.24,'build wind non-float'
    1.51655,12.75,2.85,1.44,73.27,0.57,8.79,0.11,0.22,'build wind non-float'
    1.51779,13.64,3.65,0.65,73,0.06,8.93,0,0,'vehic wind float'
    1.51837,13.14,2.84,1.28,72.85,0.55,9.07,0,0,'build wind float'
    1.51545,14.14,0,2.68,73.39,0.08,9.07,0.61,0.05,headlamps
    1.51789,13.19,3.9,1.3,72.33,0.55,8.44,0,0.28,'build wind non-float'
    1.51625,13.36,3.58,1.49,72.72,0.45,8.21,0,0,'build wind non-float'
    1.51743,12.2,3.25,1.16,73.55,0.62,8.9,0,0.24,'build wind non-float'
    1.52223,13.21,3.77,0.79,71.99,0.13,10.02,0,0,'build wind float'
    1.52121,14.03,3.76,0.58,71.79,0.11,9.65,0,0,'vehic wind float'
    1.51665,13.14,3.45,1.76,72.48,0.6,8.38,0,0.17,'vehic wind float'
    1.51707,13.48,3.48,1.71,72.52,0.62,7.99,0,0,'build wind non-float'
    1.51719,14.75,0,2,73.02,0,8.53,1.59,0.08,headlamps
    1.51629,12.71,3.33,1.49,73.28,0.67,8.24,0,0,'build wind non-float'
    1.51994,13.27,0,1.76,73.03,0.47,11.32,0,0,containers
    1.51811,12.96,2.96,1.43,72.92,0.6,8.79,0.14,0,'build wind non-float'
    1.52152,13.05,3.65,0.87,72.22,0.19,9.85,0,0.17,'build wind float'
    1.52475,11.45,0,1.88,72.19,0.81,13.24,0,0.34,'build wind non-float'
    1.51841,12.93,3.74,1.11,72.28,0.64,8.96,0,0.22,'build wind non-float'
    1.51754,13.39,3.66,1.19,72.79,0.57,8.27,0,0.11,'build wind float'
    1.52058,12.85,1.61,2.17,72.18,0.76,9.7,0.24,0.51,containers
    1.51569,13.24,3.49,1.47,73.25,0.38,8.03,0,0,'build wind non-float'
    1.5159,12.82,3.52,1.9,72.86,0.69,7.97,0,0,'build wind non-float'
    1.51683,14.56,0,1.98,73.29,0,8.52,1.57,0.07,headlamps
    1.51687,13.23,3.54,1.48,72.84,0.56,8.1,0,0,'build wind non-float'
    1.5161,13.33,3.53,1.34,72.67,0.56,8.33,0,0,'vehic wind float'
    1.51674,12.87,3.56,1.64,73.14,0.65,7.99,0,0,'build wind non-float'
    1.51832,13.33,3.34,1.54,72.14,0.56,8.99,0,0,'vehic wind float'
    1.51115,17.38,0,0.34,75.41,0,6.65,0,0,tableware
    1.51645,13.44,3.61,1.54,72.39,0.66,8.03,0,0,'build wind non-float'
    1.51755,13,3.6,1.36,72.99,0.57,8.4,0,0.11,'build wind float'
    1.51571,12.72,3.46,1.56,73.2,0.67,8.09,0,0.24,'build wind float'
    1.51596,12.79,3.61,1.62,72.97,0.64,8.07,0,0.26,'build wind float'
    1.5173,12.35,2.72,1.63,72.87,0.7,9.23,0,0,'build wind non-float'
    1.51662,12.85,3.51,1.44,73.01,0.68,8.23,0.06,0.25,'build wind non-float'
    1.51409,14.25,3.09,2.08,72.28,1.1,7.08,0,0,'build wind non-float'
    1.51797,12.74,3.48,1.35,72.96,0.64,8.68,0,0,'build wind float'
    1.51806,13,3.8,1.08,73.07,0.56,8.38,0,0.12,'build wind non-float'
    1.51627,13,3.58,1.54,72.83,0.61,8.04,0,0,'build wind non-float'
    1.5159,13.24,3.34,1.47,73.1,0.39,8.22,0,0,'build wind non-float'
    1.51934,13.64,3.54,0.75,72.65,0.16,8.89,0.15,0.24,'vehic wind float'
    1.51755,12.71,3.42,1.2,73.2,0.59,8.64,0,0,'build wind float'
    1.51514,14.01,2.68,3.5,69.89,1.68,5.87,2.2,0,containers
    1.51766,13.21,3.69,1.29,72.61,0.57,8.22,0,0,'build wind float'
    1.51784,13.08,3.49,1.28,72.86,0.6,8.49,0,0,'build wind float'
    1.52177,13.2,3.68,1.15,72.75,0.54,8.52,0,0,'build wind non-float'
    1.51753,12.57,3.47,1.38,73.39,0.6,8.55,0,0.06,'build wind float'
    1.51851,13.2,3.63,1.07,72.83,0.57,8.41,0.09,0.17,'build wind non-float'
    1.51743,13.3,3.6,1.14,73.09,0.58,8.17,0,0,'build wind float'
    1.51593,13.09,3.59,1.52,73.1,0.67,7.83,0,0,'build wind non-float'
    1.5164,14.37,0,2.74,72.85,0,9.45,0.54,0,headlamps
    1.51735,13.02,3.54,1.69,72.73,0.54,8.44,0,0.07,'build wind float'
    1.52247,14.86,2.2,2.06,70.26,0.76,9.76,0,0,headlamps
    1.52099,13.69,3.59,1.12,71.96,0.09,9.4,0,0,'build wind float'
    1.51769,13.65,3.66,1.11,72.77,0.11,8.6,0,0,'vehic wind float'
    1.51846,13.41,3.89,1.33,72.38,0.51,8.28,0,0,'build wind non-float'
    1.51848,13.64,3.87,1.27,71.96,0.54,8.32,0,0.32,'build wind non-float'
    1.51905,13.6,3.62,1.11,72.64,0.14,8.76,0,0,'build wind float'
    1.51567,13.29,3.45,1.21,72.74,0.56,8.57,0,0,'build wind float'
    1.52213,14.21,3.82,0.47,71.77,0.11,9.57,0,0,'build wind float'
    1.5232,13.72,3.72,0.51,71.75,0.09,10.06,0,0.16,'build wind float'
    1.51556,13.87,0,2.54,73.23,0.14,9.41,0.81,0.01,headlamps
    1.51926,13.2,3.33,1.28,72.36,0.6,9.14,0,0.11,'build wind float'
    1.52211,14.19,3.78,0.91,71.36,0.23,9.14,0,0.37,'vehic wind float'
    1.53125,10.73,0,2.1,69.81,0.58,13.3,3.15,0.28,'build wind non-float'
    1.52152,13.05,3.65,0.87,72.32,0.19,9.85,0,0.17,'build wind float'
    1.51829,14.46,2.24,1.62,72.38,0,9.26,0,0,tableware
    1.51892,13.46,3.83,1.26,72.55,0.57,8.21,0,0.14,'build wind non-float'
    1.51888,14.99,0.78,1.74,72.5,0,9.95,0,0,tableware
    1.51829,13.24,3.9,1.41,72.33,0.55,8.31,0,0.1,'build wind non-float'
    1.523,13.31,3.58,0.82,71.99,0.12,10.17,0,0.03,'build wind float'
    1.51652,13.56,3.57,1.47,72.45,0.64,7.96,0,0,'build wind non-float'
    1.51768,12.56,3.52,1.43,73.15,0.57,8.54,0,0,'build wind float'
    1.51215,12.99,3.47,1.12,72.98,0.62,8.35,0,0.31,'build wind float'
    1.51646,13.04,3.4,1.26,73.01,0.52,8.58,0,0,'vehic wind float'
    1.51721,12.87,3.48,1.33,73.04,0.56,8.43,0,0,'build wind float'
    1.51763,12.8,3.66,1.27,73.01,0.6,8.56,0,0,'build wind float'
    1.51742,13.27,3.62,1.24,73.08,0.55,8.07,0,0,'build wind float'
    1.52127,14.32,3.9,0.83,71.5,0,9.49,0,0,'vehic wind float'
    1.51779,13.21,3.39,1.33,72.76,0.59,8.59,0,0,'build wind float'
    1.52171,11.56,1.88,1.56,72.86,0.47,11.41,0,0,containers
    1.518,13.71,3.93,1.54,71.81,0.54,8.21,0,0.15,'build wind non-float'
    1.52777,12.64,0,0.67,72.02,0.06,14.4,0,0,'build wind non-float'
    1.5175,12.82,3.55,1.49,72.75,0.54,8.52,0,0.19,'build wind float'
    1.51764,12.98,3.54,1.21,73,0.65,8.53,0,0,'build wind float'
    1.52177,13.75,1.01,1.36,72.19,0.33,11.14,0,0,'build wind non-float'
    1.51645,14.94,0,1.87,73.11,0,8.67,1.38,0,headlamps
    1.51786,12.73,3.43,1.19,72.95,0.62,8.76,0,0.3,'build wind float'
    1.52152,13.12,3.58,0.9,72.2,0.23,9.82,0,0.16,'build wind float'
    1.51937,13.79,2.41,1.19,72.76,0,9.77,0,0,tableware
    1.51514,14.85,0,2.42,73.72,0,8.39,0.56,0,headlamps
    1.52172,13.48,3.74,0.9,72.01,0.18,9.61,0,0.07,'build wind float'
    1.51732,14.95,0,1.8,72.99,0,8.61,1.55,0,headlamps
    1.5202,13.98,1.35,1.63,71.76,0.39,10.56,0,0.18,'build wind non-float'
    1.51605,12.9,3.44,1.45,73.06,0.44,8.27,0,0,'build wind non-float'
    1.51847,13.1,3.97,1.19,72.44,0.6,8.43,0,0,'build wind non-float'
    1.51761,13.89,3.6,1.36,72.73,0.48,7.83,0,0,'build wind float'
    1.51673,13.3,3.64,1.53,72.53,0.65,8.03,0,0.29,'build wind non-float'
    1.52365,15.79,1.83,1.31,70.43,0.31,8.61,1.68,0,headlamps
    1.51685,14.92,0,1.99,73.06,0,8.4,1.59,0,headlamps
    1.51658,14.8,0,1.99,73.11,0,8.28,1.71,0,headlamps
    1.51316,13.02,0,3.04,70.48,6.21,6.96,0,0,containers
    1.51709,13,3.47,1.79,72.72,0.66,8.18,0,0,'build wind non-float'
    1.51727,14.7,0,2.34,73.28,0,8.95,0.66,0,headlamps
    1.51898,13.58,3.35,1.23,72.08,0.59,8.91,0,0,'build wind float'
    1.51969,12.64,0,1.65,73.75,0.38,11.53,0,0,containers
    1.5182,12.62,2.76,0.83,73.81,0.35,9.42,0,0.2,'build wind non-float'
    1.51617,14.95,0,2.27,73.3,0,8.71,0.67,0,headlamps
    1.51911,13.9,3.73,1.18,72.12,0.06,8.89,0,0,'build wind float'
    1.51651,14.38,0,1.94,73.61,0,8.48,1.57,0,headlamps
    1.51694,12.86,3.58,1.31,72.61,0.61,8.79,0,0,'vehic wind float'
    1.52315,13.44,3.34,1.23,72.38,0.6,8.83,0,0,headlamps
    1.52068,13.55,2.09,1.67,72.18,0.53,9.57,0.27,0.17,'build wind non-float'
    1.51838,14.32,3.26,2.22,71.25,1.46,5.79,1.63,0,headlamps
    1.51818,13.72,0,0.56,74.45,0,10.99,0,0,'build wind non-float'
    1.51769,12.45,2.71,1.29,73.7,0.56,9.06,0,0.24,'build wind float'
    1.5166,12.99,3.18,1.23,72.97,0.58,8.81,0,0.24,'build wind non-float'
    1.51589,12.88,3.43,1.4,73.28,0.69,8.05,0,0.24,'build wind float'
    1.5241,13.83,2.9,1.17,71.15,0.08,10.79,0,0,'build wind non-float'
    1.52725,13.8,3.15,0.66,70.57,0.08,11.64,0,0,'build wind non-float'
    1.52119,12.97,0.33,1.51,73.39,0.13,11.27,0,0.28,containers
    1.51748,12.86,3.56,1.27,73.21,0.54,8.38,0,0.17,'build wind float'
    1.51653,11.95,0,1.19,75.18,2.7,8.93,0,0,headlamps
    1.51623,14.14,0,2.88,72.61,0.08,9.18,1.06,0,headlamps
    1.52101,13.64,4.49,1.1,71.78,0.06,8.75,0,0,'build wind float'
    1.51763,12.61,3.59,1.31,73.29,0.58,8.5,0,0,'build wind float'
    1.51596,13.02,3.56,1.54,73.11,0.72,7.9,0,0,'build wind non-float'
    1.51674,12.79,3.52,1.54,73.36,0.66,7.9,0,0,'build wind non-float'
    1.52065,14.36,0,2.02,73.42,0,8.44,1.64,0,headlamps
    1.51768,12.65,3.56,1.3,73.08,0.61,8.69,0,0.14,'build wind float'
    1.52369,13.44,0,1.58,72.22,0.32,12.24,0,0,containers
    1.51756,13.15,3.61,1.05,73.24,0.57,8.24,0,0,'build wind float'
    1.51754,13.48,3.74,1.17,72.99,0.59,8.03,0,0,'build wind float'
    1.51711,12.89,3.62,1.57,72.96,0.61,8.11,0,0,'build wind non-float'
    1.5221,13.73,3.84,0.72,71.76,0.17,9.74,0,0,'build wind float'
    1.51594,13.09,3.52,1.55,72.87,0.68,8.05,0,0.09,'build wind non-float'
    1.51784,12.68,3.67,1.16,73.11,0.61,8.7,0,0,'build wind float'
    1.51909,13.89,3.53,1.32,71.81,0.51,8.78,0.11,0,'build wind float'
    1.51977,13.81,3.58,1.32,71.72,0.12,8.67,0.69,0,'build wind float'
    1.51666,12.86,0,1.83,73.88,0.97,10.17,0,0,containers
    1.51631,13.34,3.57,1.57,72.87,0.61,7.89,0,0,'build wind non-float'
    1.51872,12.93,3.66,1.56,72.51,0.58,8.55,0,0.12,'build wind non-float'
    1.51708,13.72,3.68,1.81,72.06,0.64,7.88,0,0,'build wind non-float'
    1.52081,13.78,2.28,1.43,71.99,0.49,9.85,0,0.17,'build wind non-float'
    1.51574,14.86,3.67,1.74,71.87,0.16,7.36,0,0.12,'build wind non-float'
    1.51813,13.43,3.98,1.18,72.49,0.58,8.15,0,0,'build wind non-float'
    1.51131,13.69,3.2,1.81,72.81,1.76,5.43,1.19,0,headlamps
    1.52227,14.17,3.81,0.78,71.35,0,9.69,0,0,'build wind float'
    1.52614,13.7,0,1.36,71.24,0.19,13.44,0,0.1,'build wind non-float'
    1.51811,13.33,3.85,1.25,72.78,0.52,8.12,0,0,'build wind non-float'
    1.51655,13.41,3.39,1.28,72.64,0.52,8.65,0,0,'vehic wind float'
    1.51751,12.81,3.57,1.35,73.02,0.62,8.59,0,0,'build wind float'
    1.51508,15.15,0,2.25,73.5,0,8.34,0.63,0,headlamps
    1.51915,12.73,1.85,1.86,72.69,0.6,10.09,0,0,containers
    1.51966,14.77,3.75,0.29,72.02,0.03,9,0,0,'build wind float'
    1.51844,13.25,3.76,1.32,72.4,0.58,8.42,0,0,'build wind non-float'
    1.52664,11.23,0,0.77,73.21,0,14.68,0,0,'build wind non-float'
    1.52172,13.51,3.86,0.88,71.79,0.23,9.54,0,0.11,'build wind float'
    1.51602,14.85,0,2.38,73.28,0,8.76,0.64,0.09,headlamps
    1.51321,13,0,3.02,70.7,6.21,6.93,0,0,containers
    1.52739,11.02,0,0.75,73.08,0,14.96,0,0,'build wind non-float'
    1.52213,14.21,3.82,0.47,71.77,0.11,9.57,0,0,'build wind float'
    1.51747,12.84,3.5,1.14,73.27,0.56,8.55,0,0,'build wind float'
    1.51839,12.85,3.67,1.24,72.57,0.62,8.68,0,0.35,'build wind non-float'
    1.51646,13.41,3.55,1.25,72.81,0.68,8.1,0,0,'build wind non-float'
    1.51609,15.01,0,2.51,73.05,0.05,8.83,0.53,0,headlamps
    1.51667,12.94,3.61,1.26,72.75,0.56,8.6,0,0,'build wind non-float'
    1.51588,13.12,3.41,1.58,73.26,0.07,8.39,0,0.19,'build wind non-float'
    1.52667,13.99,3.7,0.71,71.57,0.02,9.82,0,0.1,'build wind float'
    1.51831,14.39,0,1.82,72.86,1.41,6.47,2.88,0,headlamps
    1.51918,14.04,3.58,1.37,72.08,0.56,8.3,0,0,'build wind float'
    1.51613,13.88,1.78,1.79,73.1,0,8.67,0.76,0,headlamps
    1.52196,14.36,3.85,0.89,71.36,0.15,9.15,0,0,'build wind float'
    1.51824,12.87,3.48,1.29,72.95,0.6,8.43,0,0,'build wind float'
    1.52151,11.03,1.71,1.56,73.44,0.58,11.62,0,0,containers
    1.51969,14.56,0,0.56,73.48,0,11.22,0,0,tableware
    1.51618,13.01,3.5,1.48,72.89,0.6,8.12,0,0,'build wind non-float'
    1.51645,13.4,3.49,1.52,72.65,0.67,8.08,0,0.1,'build wind non-float'
    1.51796,13.5,3.36,1.63,71.94,0.57,8.81,0,0.09,'vehic wind float'
    1.52222,14.43,0,1,72.67,0.1,11.52,0,0.08,'build wind non-float'
    1.51783,12.69,3.54,1.34,72.95,0.57,8.75,0,0,'build wind float'
    1.51711,14.23,0,2.08,73.36,0,8.62,1.67,0,headlamps
    1.51736,12.78,3.62,1.29,72.79,0.59,8.7,0,0,'build wind float'
    1.51808,13.43,2.87,1.19,72.84,0.55,9.03,0,0,'build wind float'
    1.5167,13.24,3.57,1.38,72.7,0.56,8.44,0,0.1,'vehic wind float'
    1.52043,13.38,0,1.4,72.25,0.33,12.5,0,0,containers
    1.519,13.49,3.48,1.35,71.95,0.55,9,0,0,'build wind float'
    1.51778,13.21,2.81,1.29,72.98,0.51,9.02,0,0.09,'build wind float'
    1.51905,14,2.39,1.56,72.37,0,9.57,0,0,tableware
    1.51531,14.38,0,2.66,73.1,0.04,9.08,0.64,0,headlamps
    1.51916,14.15,0,2.09,72.74,0,10.88,0,0,tableware
    1.51841,13.02,3.62,1.06,72.34,0.64,9.13,0,0.15,'build wind non-float'
    1.5159,13.02,3.58,1.51,73.12,0.69,7.96,0,0,'build wind non-float'
    1.51593,13.25,3.45,1.43,73.17,0.61,7.86,0,0,'build wind non-float'
    1.5164,12.55,3.48,1.87,73.23,0.63,8.08,0,0.09,'build wind non-float'
    1.51663,12.93,3.54,1.62,72.96,0.64,8.03,0,0.21,'build wind non-float'
    1.5169,13.33,3.54,1.61,72.54,0.68,8.11,0,0,'build wind non-float'
    1.51869,13.19,3.37,1.18,72.72,0.57,8.83,0,0.16,'build wind float'
    1.51776,13.53,3.41,1.52,72.04,0.58,8.79,0,0,'vehic wind float'
    1.51775,12.85,3.48,1.23,72.97,0.61,8.56,0.09,0.22,'build wind float'
    1.5186,13.36,3.43,1.43,72.26,0.51,8.6,0,0,'build wind non-float'
    1.5172,13.38,3.5,1.15,72.85,0.5,8.43,0,0,'build wind float'
    1.51623,14.2,0,2.79,73.46,0.04,9.04,0.4,0.09,headlamps
    1.51618,13.53,3.55,1.54,72.99,0.39,7.78,0,0,'build wind float'
    1.51761,12.81,3.54,1.23,73.24,0.58,8.39,0,0,'build wind float'
    1.5161,13.42,3.4,1.22,72.69,0.59,8.32,0,0,'vehic wind float'
    1.51592,12.86,3.52,2.12,72.66,0.69,7.97,0,0,'build wind non-float'
    1.51613,13.92,3.52,1.25,72.88,0.37,7.94,0,0.14,'build wind non-float'
    1.51689,12.67,2.88,1.71,73.21,0.73,8.54,0,0,'build wind non-float'
    1.51852,14.09,2.19,1.66,72.67,0,9.32,0,0,tableware
    

     

    参考:

    https://blog.csdn.net/qq_39856931/article/details/106923716

    参考:
    https://qinjiangbo.com/dataset-format-of-weka-ARFF.html

     

    展开全文
  • WEKA入门教程以及所用的数据集大全

    热门讨论 2013-11-12 11:35:00
    weka入门教程以及本论文所用到的所有的数据集(bank-data.csv bank-data-final.arff bank-data训练集 bank-data预测集),以及我自己的运行结果等!
  • WeKa 数据集

    千次阅读 2020-01-02 20:09:12
    今天找weka官方数据集差点被自己蠢哭,写个博客纪念一下。最近在学习weka的基本操作,来训练自己的数据进行分类等操作,网上找了一个视频Weka讲解视频 YouTobe视频 ...

    今天找weka官方数据集差点被自己蠢哭,写个博客纪念一下。最近在学习weka的基本操作,来训练自己的数据进行分类等操作,网上找了一个视频Weka讲解视频

    YouTobe视频 “https://www.youtube.com/watch?v=LcHw2ph6bss&list=PLm4W7_iX_v4NqPUjceOGd-OKNVO4c_cPD”
    哔哩哔哩视频"https://www.bilibili.com/video/av45489204?p=11"
    weka官网:“https://www.cs.waikato.ac.nz/ml/weka/”

    可以下载安装包和教程等

    数据

    今天下午各大网站找了一下午的数据集,都没找到视频里面提到的数据集。最后看的有个读者提了一个问题,也是关于找不到数据集的问题。在这里插入图片描述
    问题:I have installed WEKA on my Mac ,I’m not able to find the data sets, to open in weka in my Mac. Where could I find them?

    回答:The datasets will be in the ‘data’ folder where Weka was installed. For example: C:\Program Files\Weka-3-8\data

    关键 也就是在自己安装包下的data目录下:例如我的目录:D:\Weka-3-8\data在这里插入图片描述
    数据集链接:https://pan.baidu.com/s/1U0Sk5lDjdWJhifkMx1Zsdg
    提取码:kcbv

    向林
    2020年1月2日于长沙

    展开全文
  • WEKA数据集

    千次阅读 2018-09-30 15:21:46
    WEKA数据集WEKA所处理的数据集是一个.arff(attribute relation file)为后缀名的二维表。这是一种ASCII文本文件。以%开始的行是注释。 表中具体的内容: @relation+文件名称 @attribute+属性名和具体的属性值 @...

    WEKA数据集:

    WEKA所处理的数据集是一个.arff(attribute relation file)为后缀名的二维表。这是一种ASCII文本文件。以%开始的行是注释。
    表中具体的内容:
    @relation+文件名称
    @attribute+属性名和具体的属性值
    @data后为每个实例对应的属性值

    1、@relation<关系名>,此处关系名是一个字符串 ,如果字符串包含空格,必须加上引号(之英文标点的单引号或者双引号)

    2、 属性声明:一系列@attribute开头的语句来表示。数据集中每一个属性都有对应的@attribute来定义它的属性名称和数据类型。
    @attribute<属性名><数据类型>:
    属性名必须是以字母开头的字符串,和关系名称一样,如果这个字符串包含空格,它必须加上引号。
    属性声明语句是顺序很重要,最后一个声明的属性被称class值,在分类或者回归任务中,被默认为目标变量。

    3、@data 数据信息:每个实例占一行,实例的各属性值用逗号隔开,某各属性值缺失,用问号表示,切问号不能省略。

    4、WEKA支持的数据类型

    • numeric数值型、:整数或者实数
    • nominal-specification标称型、 如:Outlook{sunny,overcast,rainy} 打括号中的就是类别
    • string字符串型、 :可以包含任意文本。
    • data[data-formal]日期和时间型。 :默认日期格式:ISO-8601给出的格式:“yyyy-MM-dd HH:mm:ss”
    • 还可以使用integer和real类型,但是WEKA把他们都当做numeric类型看待。
      注: integer和real、numeric和string,data是区分大小写的,但是relation、attribute‘data不区分大小写。

    稀疏数据

    有时候数据集中含所有大量的0值,这时候用稀疏数据更加节省存储空间。在这里插入图片描述

    展开全文
  • weka数据集进行分类

    2021-10-29 12:16:43
    (3)打开weka文件中的data文件夹,其中有weka自带数据集 (4)这里以weather.nominal.arff数据集为例,选择打开 (5)下图为打开数据集后的示意图,继续点击分类功能 (6)选择分类器 (7)...
  • 数据集是来源于 University of California, Irvine(UCI)机器学习数据库中的 Pima Indian Diabetes 数据集,总共包含 768 条数据项。...数据集已转arff格式(其实与csv格式差不多可自行修改),可用于weka
  • Weka几乎包含了所有常见机器学习算法的Java实现,Weka中支持的数据格式主要是arff,虽然weka官网上提供了一些arff文件,但有时仅有这些还不能满足需求,为此,本人搜集各方资料,再加上自己的手工转换,整理出了一个...
  • 学习weka(7):weka数据预处理方法

    千次阅读 2021-04-11 09:30:58
    weka 数据预处理阶段全部在 filter 上: 下面把一些常见的机器学习数据与处理方法处理说一下(下面所有实例都是在 Explorer 模块上进行的)。 2、数据预处理方法 可以看到其 filters 可以分为五类,重点是画红框的...
  • There are 4 attributes and 3 species of iris 在Weka中打开iris.arff 点击Edit就会弹出数据 可以编辑更改具体的数据 还可以remove attribute visualize one attribute
  • 数据挖掘的weka包和数据集

    千次阅读 2018-03-26 13:15:34
    weka链接:https://pan.baidu.com/s/1SrlaErxMqpBoya7_HAkuHQ 密码:kzfb数据集链接:https://pan.baidu.com/s/1wDUGoh30pUdQ6bGkwTVhlw 密码:8hsz
  • 只有一个数据集可以按照百分比分割(数据分割是随机的) 不同分割会带来不同结果。运行前wake会初始化随机数生成器,确保相同分割结果同。可以设置随机数修改相同分割的结果。 设置随机种子(做交叉验证或...
  • 压缩包共有20个.arff数据集,来自于机器学习数据挖掘开源软件Weka自带数据集
  • 使用Weka软件开展医疗领域的应用研究,为相关研究人员提供参考
  • 01Seaborn自带数据集在学习Pandas透视表的时候,大家应该注意到,我们使用的案例数据"泰坦尼克号"来自于seaborn自带的在线数据库,我们可以通过seaborn提供的函数load_dataset("数据集名称")来获取线上相应的数据,...
  • WEKA入门用的银行数据集bank-data.arff

    热门讨论 2013-12-22 17:09:50
    用于weka初入门学习,银行数据包括600实例,是data-bank.arff 文件,经过csv 处理之后的可经weka使用的文件。-The learn for weka early entry, bank data including 600 instances of the the the data-bank.arff ...
  • 这是一个鸢尾花的特征(sepal_length:花萼长度;sepal_width:花萼宽度;petal_length:花瓣长度;petal_width:花瓣宽度)和标签(setosa(山...virginica(弗吉尼亚鸢尾))数据,用来KNN,感知器算法的实现的测试数据
  • diabetes prediction dataset ...在weka中打开 How to use Weka to run a classifier(a classificationmodel) Choose classifier 这个就是C4.5算法的实现(一个分类决策树算法) 可以...
  • weka数据集预处理

    千次阅读 2016-09-27 17:52:58
    1. 利用有监督的离散算法对数据集的属性进行离散,并保存离散后的数据集; import java.io.File; import weka.filters.SupervisedFilter; import java.io.IOException; import weka.core.Instances; import ...
  • Weka之训练与测试数据

    千次阅读 2019-10-27 22:40:12
    训练集和测试集应来源于同一个数据集,但为两个不相交的集合。比如:将一个数据集的1/3作为测试集,2/3作为训练集。 接下来通过一个简单的实验进一步理解训练与测试数据: 1、打开Explorer界面,选择数据集segment...
  • 数据挖掘是很多技术的共同术语,用以表达从数据中一点点地收集信息并将其转变成有实际意义的趋势和规则来提高您对数据的理解。...用 WEKA 进行数据挖掘,第 1 部分:简介和回归,我介绍了数据挖掘的概念以及免费的开源
  • Weka简单介绍

    千次阅读 2015-03-27 04:46:40
     如果要做一个简单的classifier的训练,首先我们打开一个weka自带的dataset :breast-cancer.arff,这是一个关于患者乳腺癌是否复发的dataset,数据比较简单,每一个instance代表一个病人,有9个attributes,包括...
  • Weka -- 数据格式基本介绍

    万次阅读 2011-12-26 15:21:29
    Weka是什么不多介绍,直接切入正题,简单介绍Weka的数据格式。 Weka存储数据的格式是ARFF...如下例,weka自带的weather.arff文件。 % ARFF file for the weather data with some numric features  %  @relatio
  •  weka.*; import  weka.classifiers.trees.J48; import  weka.core.Attribute; import  weka.core.Instance; import  weka.core.Instances; import  weka.core.converters.ConverterUtils.DataSource; ...
  • Java调用Weka实现决策树分类,算法为J48,数据为Iris,绝对好用。
  • 盘点 | Python自带的那些数据集

    千次阅读 2019-09-30 00:45:59
    01Seaborn自带数据集在学习Pandas透视表的时候,大家应该注意到,我们使用的案例数据"泰坦尼克号"来自于seaborn自带的在线数据库,我们可以通过seabo...

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