R语言-Rattle数据挖掘

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Rattle包是基于R语言的图形用户界面GUI可视化数据挖掘工具，避免代码书写，功能丰富，还可通过Log查看日志，学习代码，接下来通过10篇文章学习Rattle包在数据挖掘中的应用。

1
初识Rattle

载入和启动Rattle，第一行为菜单栏，第二行工具栏，第三行选项卡，选项卡分别有：Data(输入数据)、Explore(数据探索)、Test(统计检验)、Transform(数据转换)、Cluster(聚类分析)、Associate(关联规则)、Model(模型)、Evaluate(模型评估)。

R语言-Rattle数据挖掘（2）

2
Data选项卡

数据来源选择和输入，格式有TXT、CSV、Excel、SQL等以及R语言包自带的数据集。

R语言-Rattle数据挖掘（2）

R语言-Rattle数据挖掘（2）

30
Explore选项卡，数据探索-相关分析

Ordered 按相关强弱排序

Explore missing 缺失值相关分析

Hierarchical 层次相关

Method 提供Pearson、Spearman和Kendall三种方法

R语言-Rattle数据挖掘（2）

相关矩阵 
    
      
      
    
    
     
       
       
     
  1. orrelation summary using the 'Pearson' covariance.
    2. 
     
       
       
     
  2. Note that only correlations between numeric variables are reported.
    3. 
     
       
       
     
  3.               Pressure3pm Pressure9am Humidity9am WindSpeed3pm Humidity3pm    Sunshine    Cloud3pm WindSpeed9am
    4. 
     
       
       
     
  4. Pressure3pm    1.00000000  0.96897642   0.1521277 -0.335226602 -0.01580015 -0.06813014 -0.07554600  -0.29297114
    5. 
     
       
       
     
  5. Pressure9am    0.96897642  1.00000000   0.1524648 -0.371372978 -0.09012507 -0.01836370 -0.07673340  -0.40059684
    6. 
     
       
       
     
  6. Humidity9am    0.15212768  0.15246484   1.0000000 -0.344325106  0.49552358 -0.46823913  0.27819872  -0.34034116
    7. 
     
       
       
     
  7. WindSpeed3pm  -0.33522660 -0.37137298  -0.3443251  1.000000000 -0.05553257  0.12503533 -0.07077685   0.49130778
    8. 
     
       
       
     
  8. Humidity3pm   -0.01580015 -0.09012507   0.4955236 -0.055532570  1.00000000 -0.75751258  0.53217454   0.12861487
    9. 
     
       
       
     
  9. Sunshine      -0.06813014 -0.01836370  -0.4682391  0.125035331 -0.75751258  1.00000000 -0.67080423  -0.05329541
    10. 
     
       
       
     
  10. Cloud3pm      -0.07554600 -0.07673340   0.2781987 -0.070776854  0.53217454 -0.67080423  1.00000000  -0.04738166
    11. 
     
       
       
     
  11. WindSpeed9am  -0.29297114 -0.40059684  -0.3403412  0.491307778  0.12861487 -0.05329541 -0.04738166   1.00000000
    12. 
     
       
       
     
  12. Rainfall      -0.23702286 -0.31098103   0.1930967  0.045300192  0.31217242 -0.15507662  0.09317110   0.17305783
    13. 
     
       
       
     
  13. WindGustSpeed -0.51159855 -0.53119422  -0.4027873  0.657349969 -0.08627584  0.12253949 -0.02771644   0.54032660
    14. 
     
       
       
     
  14. Cloud9am      -0.12196717 -0.15234691   0.3898705 -0.060765345  0.53367655 -0.66867659  0.51027937   0.10673849
    15. 
     
       
       
     
  15. Evaporation   -0.42083515 -0.40044671  -0.4513420  0.057763791 -0.37115619  0.27051093 -0.10184521   0.10623752
    16. 
     
       
       
     
  16. Temp3pm       -0.34293423 -0.24726344  -0.3230771 -0.165244193 -0.56336278  0.45661908 -0.17393142  -0.17167422
    17. 
     
       
       
     
  17. MaxTemp       -0.37424892 -0.28151629  -0.3272456 -0.152145582 -0.52004926  0.43511216 -0.14324702  -0.15023725
    18. 
     
       
       
     
  18. Temp9am       -0.50426161 -0.46699389  -0.4187603  0.005536074 -0.23955741  0.20529853  0.01937453   0.13911180
    19. 
     
       
       
     
  19. MinTemp       -0.52804603 -0.52592375  -0.1978675 -0.047049560 -0.04346591  0.03885863  0.09272276   0.19917684
    20.

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相关图

R语言-Rattle数据挖掘（2）

缺失值相关分析 
  
    
    
  
    
   
     
     
   
  1. Missing values correlation summary using the 'Pearson' covariance.
    2. 
   
     
     
   
  2. Note that only correlations between numeric variables are reported.
    3. 
   
     
     
   
  3.                WindDir9am WindSpeed9am  WindGustDir WindGustSpeed     Sunshine   WindDir3pm
    4. 
   
     
     
   
  4. WindDir9am     1.00000000  0.400999442 -0.027879443  -0.027879443 -0.027879443 -0.019675051
    5. 
   
     
     
   
  5. WindSpeed9am   0.40099944  1.000000000 -0.011179641  -0.011179641 -0.011179641 -0.007889684
    6. 
   
     
     
   
  6. WindGustDir   -0.02787944 -0.011179641  1.000000000   1.000000000 -0.007874016 -0.005556842
    7. 
   
     
     
   
  7. WindGustSpeed -0.02787944 -0.011179641  1.000000000   1.000000000 -0.007874016 -0.005556842
    8. 
   
     
     
   
  8. Sunshine      -0.02787944 -0.011179641 -0.007874016  -0.007874016  1.000000000 -0.005556842
    9. 
   
     
     
   
  9. WindDir3pm    -0.01967505 -0.007889684 -0.005556842  -0.005556842 -0.005556842  1.000000000
    10. 
   
     
     
   
  10. Count of missing values:
    11. 
   
     
     
   
  11.    WindDir9am  WindSpeed9am   WindGustDir WindGustSpeed      Sunshine    WindDir3pm 
    12. 
   
     
     
   
  12.            23             4             2             2             2             1 
    13. 
   
     
     
   
  13. Percent missing values:
    14. 
   
     
     
   
  14.    WindDir9am  WindSpeed9am   WindGustDir WindGustSpeed      Sunshine    WindDir3pm 
    15. 
   
     
     
   
  15.      8.984375      1.562500      0.781250      0.781250      0.781250      0.390625 
    16.

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R语言-Rattle数据挖掘（2）

相关树

R语言-Rattle数据挖掘（2）

3
Explore选项卡，数据探索-主成分分析

PCA分析主要有两种方法SVD和Eigen

R语言-Rattle数据挖掘（2）

SVD 
   
     
     
   
    
    
      
      
    
  1. Note that principal components on only the numeric
    2. 
    
      
      
    
  2.  variables is calculated, and so we can not use this
    3. 
    
      
      
    
  3.  approach to remove categoric variables from  consideration.
    4. 
    
      
      
    
  4.  Any numeric variables with relatively large rotation
    5. 
    
      
      
    
  5.  values (negative or positive) in any of the first few
    6. 
    
      
      
    
  6.  components are generally variables that you may wish
    7. 
    
      
      
    
  7.  to include in the modelling.
    8. 
    
      
      
    
  8. Rattle timestamp: 2018-06-07 21:39:35 lenovo
    9. 
    
      
      
    
  9. ======================================================================
    10. 
    
      
      
    
  10. Standard deviations (1, .., p=16):
    11. 
    
      
      
    
  11.  [1] 2.33967160 1.84564685 1.60151562 1.04888312 0.91136037 0.74777048 0.70891475 0.61316523 0.57853049 0.54903515
    12. 
    
      
      
    
  12. [11] 0.51134869 0.41714578 0.25534947 0.16579137 0.12937785 0.07205772
    13. 
    
      
      
    
  13. Rotation (n x k) = (16 x 16):
    14. 
    
      
      
    
  14.                        PC1         PC2         PC3          PC4          PC5         PC6         PC7         PC8
    15. 
    
      
      
    
  15. MinTemp        0.332147794 -0.19888150  0.24374707 -0.052744720  0.207808523 -0.12719510  0.01875075  0.18136991
    16. 
    
      
      
    
  16. MaxTemp        0.374029936  0.08978966  0.25057780 -0.006974787 -0.036994995  0.09067259  0.12047779  0.21047458
    17. 
    
      
      
    
  17. Rainfall       0.005796511 -0.25554583  0.01754559  0.585240095  0.544974867  0.48892975  0.09545233 -0.16588758
    18. 
    
      
      
    
  18. Evaporation    0.348472780 -0.02048528  0.09026961 -0.161590857  0.059263540 -0.02594145 -0.01248408 -0.68057351
    19. 
    
      
      
    
  19. Sunshine       0.218371365  0.36037787 -0.18669096  0.256521413 -0.004101546  0.01273087  0.05448771  0.10851966
    20. 
    
      
      
    
  20. WindGustSpeed  0.188224533 -0.20441561 -0.38364279 -0.144862912 -0.093542976  0.19662453  0.32565177  0.18575153
    21. 
    
      
      
    
  21. WindSpeed9am   0.086750984 -0.24575847 -0.36845432 -0.166720410  0.461501526 -0.38339748 -0.14748703  0.26435578
    22. 
    
      
      
    
  22. WindSpeed3pm   0.075386096 -0.14471982 -0.48804476 -0.137773961 -0.138697649  0.25696715  0.37900970  0.02298519
    23. 
    
      
      
    
  23. Humidity9am   -0.243316473 -0.13077267  0.27770716  0.362756478 -0.223368987 -0.18594937  0.42312175  0.28779029
    24. 
    
      
      
    
  24. Humidity3pm   -0.224835150 -0.37901853  0.09367538  0.005465963  0.086236542 -0.04818380 -0.28727836  0.18277319
    25. 
    
      
      
    
  25. Pressure9am   -0.237936069  0.34351977  0.13456113 -0.307122274  0.306484944  0.16764059  0.22298428  0.11040901
    26. 
    
      
      
    
  26. Pressure3pm   -0.258224380  0.30461863  0.09483106 -0.298771321  0.425280514  0.12925818  0.18128684  0.07443856
    27. 
    
      
      
    
  27. Cloud9am      -0.089521297 -0.37057282  0.22700819 -0.207758157  0.071852259 -0.28418390  0.53207698 -0.28589005
    28. 
    
      
      
    
  28. Cloud3pm      -0.114456565 -0.31894009  0.21867635 -0.346637284 -0.234379494  0.56050810 -0.22324504  0.09488563
    29. 
    
      
      
    
  29. Temp9am        0.375914164 -0.09688413  0.19441676 -0.128195493  0.141112838  0.04927045 -0.07243403  0.23761276
    30. 
    
      
      
    
  30. Temp3pm        0.369481076  0.11693260  0.25142433 -0.004520988 -0.042580507  0.07041527  0.13823540  0.18508703
    31. 
    
      
      
    
  31.                       PC9        PC10         PC11        PC12        PC13         PC14         PC15         PC16
    32. 
    
      
      
    
  32. MinTemp        0.08078127  0.18472249 -0.071354795  0.08848297  0.65167895 -0.427155392 -0.185966311  0.004509560
    33. 
    
      
      
    
  33. MaxTemp       -0.02220307 -0.02077306  0.019804938 -0.08087304 -0.39131782 -0.246433650  0.117999554 -0.696531904
    34. 
    
      
      
    
  34. Rainfall      -0.07572417 -0.06514432  0.022858510 -0.07646998 -0.04367026 -0.001263031 -0.029692514  0.005543731
    35. 
    
      
      
    
  35. Evaporation    0.45036006 -0.05387560 -0.352121100  0.16019128 -0.11265621  0.088853684 -0.018225071 -0.008351970
    36. 
    
      
      
    
  36. Sunshine      -0.19403416 -0.02822325 -0.047410828  0.81369837  0.01445786  0.058687569 -0.005428731  0.019475811
    37. 
    
      
      
    
  37. WindGustSpeed  0.45803701 -0.41063378  0.417925346  0.06313608  0.09226322  0.021222021  0.003948858  0.024704188
    38. 
    
      
      
    
  38. WindSpeed9am  -0.13608359 -0.31666134 -0.381733019 -0.02487819 -0.22644305 -0.003588899 -0.021421866 -0.005354006
    39. 
    
      
      
    
  39. WindSpeed3pm  -0.10393634  0.59330840 -0.335728647 -0.07667309 -0.04879505 -0.053601702  0.007195032 -0.006477316
    40. 
    
      
      
    
  40. Humidity9am    0.29717693 -0.12886774 -0.467789672  0.03175672  0.03311327  0.206147706  0.005105644 -0.016727725
    41. 
    
      
      
    
  41. Humidity3pm    0.39460988  0.42031750  0.196685033  0.37789673 -0.37480362 -0.111727327  0.041353512  0.052443048
    42. 
    
      
      
    
  42. Pressure9am    0.11515092  0.02322775 -0.009386425  0.03231424 -0.15601728  0.031952713 -0.699058259 -0.004988305
    43. 
    
      
      
    
  43. Pressure3pm    0.15302204  0.03815021 -0.071446771  0.06526793  0.15789523 -0.022776258  0.668281615  0.002740504
    44. 
    
      
      
    
  44. Cloud9am      -0.41239410 -0.02562913  0.270866448  0.23001946 -0.10303812  0.021283109  0.033417558  0.003660992
    45. 
    
      
      
    
  45. Cloud3pm      -0.22935868 -0.29575615 -0.295837253  0.24151009  0.05414153 -0.015390752  0.006709164  0.010878829
    46. 
    
      
      
    
  46. Temp9am       -0.04721686  0.22844725  0.102141691 -0.05602486  0.08440026  0.797188323  0.019769059 -0.003223984
    47. 
    
      
      
    
  47. Temp3pm       -0.04521188 -0.03175603 -0.025201376 -0.13430980 -0.36563554 -0.222290018  0.105601136  0.714463175
    48. 
    
      
      
    
  48. Rattle timestamp: 2018-06-07 21:39:35 lenovo
    49. 
    
      
      
    
  49. ======================================================================
    50. 
    
      
      
    
  50. Importance of components:
    51. 
    
      
      
    
  51.                           PC1    PC2    PC3     PC4     PC5     PC6     PC7    PC8     PC9    PC10    PC11    PC12
    52. 
    
      
      
    
  52. Standard deviation     2.3397 1.8456 1.6015 1.04888 0.91136 0.74777 0.70891 0.6132 0.57853 0.54904 0.51135 0.41715
    53. 
    
      
      
    
  53. Proportion of Variance 0.3421 0.2129 0.1603 0.06876 0.05191 0.03495 0.03141 0.0235 0.02092 0.01884 0.01634 0.01088
    54. 
    
      
      
    
  54. Cumulative Proportion  0.3421 0.5550 0.7153 0.78409 0.83600 0.87095 0.90236 0.9259 0.94678 0.96562 0.98196 0.99284
    55. 
    
      
      
    
  55.                           PC13    PC14    PC15    PC16
    56. 
    
      
      
    
  56. Standard deviation     0.25535 0.16579 0.12938 0.07206
    57. 
    
      
      
    
  57. Proportion of Variance 0.00408 0.00172 0.00105 0.00032
    58. 
    
      
      
    
  58. Cumulative Proportion  0.99691 0.99863 0.99968 1.00000
    59.

（左右滑动查看）

R语言-Rattle数据挖掘（2）

碎石图

R语言-Rattle数据挖掘（2）

Biplot

Eigen 
 
   
   
 
    
  
    
    
  
  1. Note that principal components on only the numeric
    2. 
  
    
    
  
  2.  variables is calculated, and so we can not use this
    3. 
  
    
    
  
  3.  approach to remove categoric variables from  consideration.
    4. 
  
    
    
  
  4.  Any numeric variables with relatively large rotation
    5. 
  
    
    
  
  5.  values (negative or positive) in any of the first few
    6. 
  
    
    
  
  6.  components are generally variables that you may wish
    7. 
  
    
    
  
  7.  to include in the modelling.
    8. 
  
    
    
  
  8. Rattle timestamp: 2018-06-07 21:45:16 lenovo
    9. 
  
    
    
  
  9. ======================================================================
    10. 
  
    
    
  
  10. Call:
    11. 
  
    
    
  
  11. princomp(x = na.omit(crs$dataset[crs$sample, crs$numeric]), scale = TRUE, 
    12. 
  
    
    
  
  12.     center = TRUE, tol = 0)
    13. 
  
    
    
  
  13. Standard deviations:
    14. 
  
    
    
  
  14.     Comp.1     Comp.2     Comp.3     Comp.4     Comp.5     Comp.6     Comp.7     Comp.8     Comp.9    Comp.10    Comp.11 
    15. 
  
    
    
  
  15. 19.9174830 16.3408647 11.6265265  8.8919459  6.1518937  5.7172999  4.9462589  3.5038361  2.9584418  2.0621626  1.6979344 
    16. 
  
    
    
  
  16.    Comp.12    Comp.13    Comp.14    Comp.15    Comp.16 
    17. 
  
    
    
  
  17.  1.5068325  1.4106266  0.9628544  0.8071719  0.4799053 
    18. 
  
    
    
  
  18.  16  variables and  248 observations.
    19. 
  
    
    
  
  19. Rattle timestamp: 2018-06-07 21:45:16 lenovo
    20. 
  
    
    
  
  20. ======================================================================
    21. 
  
    
    
  
  21. Importance of components:
    22. 
  
    
    
  
  22.                           Comp.1     Comp.2     Comp.3     Comp.4     Comp.5     Comp.6     Comp.7     Comp.8
    23. 
  
    
    
  
  23. Standard deviation     19.917483 16.3408647 11.6265265 8.89194591 6.15189367 5.71729995 4.94625893 3.50383612
    24. 
  
    
    
  
  24. Proportion of Variance  0.393868  0.2651135  0.1342091 0.07850105 0.03757504 0.03245367 0.02429045 0.01218904
    25. 
  
    
    
  
  25. Cumulative Proportion   0.393868  0.6589816  0.7931906 0.87169168 0.90926672 0.94172039 0.96601084 0.97819988
    26. 
  
    
    
  
  26.                             Comp.9     Comp.10     Comp.11     Comp.12     Comp.13      Comp.14      Comp.15
    27. 
  
    
    
  
  27. Standard deviation     2.958441775 2.062162622 1.697934421 1.506832546 1.410626603 0.9628544018 0.8071719179
    28. 
  
    
    
  
  28. Proportion of Variance 0.008689762 0.004222092 0.002862356 0.002254301 0.001975632 0.0009204561 0.0006468654
    29. 
  
    
    
  
  29. Cumulative Proportion  0.986889637 0.991111729 0.993974085 0.996228385 0.998204017 0.9991244732 0.9997713386
    30. 
  
    
    
  
  30.                             Comp.16
    31. 
  
    
    
  
  31. Standard deviation     0.4799052997
    32. 
  
    
    
  
  32. Proportion of Variance 0.0002286614
    33. 
  
    
    
  
  33. Cumulative Proportion  1.0000000000
    34.

(左右滑动查看)

R语言-Rattle数据挖掘（2）

碎石图

R语言-Rattle数据挖掘（2）

Biplot

4
Explore选项卡，数据探索-交互式数据探索

执行后，会安装GGobi和GGRaptR，具体操作可查看官网帮助文件。

R语言-Rattle数据挖掘（2）


R语言-Rattle数据挖掘（2）


微信ID： YXSJFX2018

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