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#请先确认datasets包已经被加载，如果没有，请先自行加载程序包
__________(mtcars) #填写适当函数名查看数据维度(2分)
mtcars=________(mtcars) #将所有数据进行z-score规范化(2分)
mtcars=___________(mtcars) #将mtcars转化成数据框格式 (2分)
plot(___________) #以油耗为Y轴，排量为X轴，其余为默认参数，画散点图（4分）
mx=___________(mpg~hp,data=mtcars)#填写适当函数名建立线性回归函数(2分)
__________(mx)#显示回归结果(2分)
cat("回归模型中hp的系数是",_____________) #将答案数字填入划线处(3分)
cat("残差中位数是",_____________) #将答案数字填入划线处(3分)

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#填写答案时请删除掉下划线
#请先自行设置好工作路径
__________(wine.rdata)#读取wine.rdata数据集(2分)
_________(wine$class) #查看class列中各类别的记录条数(2分)
cat("class中属于第1类的样本有",__________,"条") #将答案数字填入划线处(3分)
wine=__________(wine,select=-class)#删除掉数据集的第1列(2分)
wine=scale(wine)
___________(factoextra)#加载factoextra程序包(2分)
fviz_nbclust(wine,________,method="silhouette") #用k均值方法确定聚类的簇数(2分)
____________(119) #设置种子数为119 （2分）
kjl=kmeans(wine,_________) #根据上一步的的结果在下划线处填写聚类的簇数(3分)
summary(kjl)
cat("第2类中Magnesium参数的均值是",__________) #根据summary的结果填写答案在下划线处(2分)
cat("第66条记录的聚类结果是第",_____,"类") #根据summary的结果填写答案在下划线处(2分)

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library(arules)
data(Epub)
inspect(________(Epub)) #填写适当的函数名来查看Epub数据集的前6行数据(2分)
sort(____________(Epub),decreasing = T)#计算每个属性的支持度，并按降序排序(2分)
cat("出现最频繁的项是","____________") #根据上一步的显示结果，将出现最频繁的项的名称填写在下划线处(2分)
gl=________(Epub,parameter=list(support=0.001,confidence=0.1,minlen=2)) #设置支持度为0.001，置信度为0.1，进行关联规则挖掘。在下划线处填写合适的函数名(2分)
summary(gl)
cat("规则lhs + rhs是3项的有",_______,"条") #根据显示结果，在下划线处填写3-项集规则有多少条(2分)
____________(gl[1:10]) #查看前10条规则(2分)
cat("第6条规则的提升度值为",_____________) #根据上一步的显示结果，在下划线处填写第6条规则的提升度(2分)

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#填写答案时请删除掉下划线
#请先自行设置好工作路径
wine=__________("wine.csv") #读取wine.csv文件到wine变量中(2分)
y=eigen(________(wine))#利用相关系数矩阵计算特征值与特征向量(2分)
sum(___________)/sum(y$values)#计算前五个主成分的累计贡献率(2分)
cat("前五个主成分的累计贡献率是",____________)#根据上一步的计算结果， 将累计贡献率填写在下划线处。(2分)

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Alcohol,"Malic_acid,Ash",Alcalinity_ash,Magnesium,Total_phenols,Flavanoids,Nonflavanoid_phenols,Proanthocyanins,Color_intensity,Hue,OD280/OD315_diluted wines,Proline
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-0.284072972,0.048025666,-0.315359006,0.001514024,-0.962127701,-1.446210502,-1.521005609,0.94932018,-1.66136831,2.088572931,-1.695090274,-1.382674123
1.428115451,0.155442234,0.413652722,0.151234178,-0.61204853,-0.982841462,-1.330788512,0.627914584,-0.613074942,2.002302725,-1.476340406,-1.269996547
0.873809846,2.966175769,0.304300963,0.300954331,-0.331985192,-0.982841462,-1.420891348,1.270725776,-0.927562952,1.13959635,-1.388840458,-1.227742457
0.491954874,1.40863553,0.413652722,1.049555099,0.158125648,-0.791102548,-1.280731381,0.547563185,-0.316058487,0.967055075,-1.126340616,-1.481267001
0.331822144,1.739836615,-0.388260179,0.151234178,1.418410667,-1.126645647,-1.340799938,0.547563185,-0.420887824,2.217979318,-1.607590327,-1.481267001
0.208643121,0.22705328,0.012696272,0.151234178,1.418410667,-1.03077619,-1.350811364,1.351077175,-0.228700707,1.82976145,-1.563840353,-1.39675882
1.391161744,1.578711763,1.361367968,1.498715559,-0.261969358,-0.391646479,-1.270719955,1.592131372,-0.420887824,1.786626131,-1.520090379,-1.424928213
1 Alcohol Malic_acid,Ash Alcalinity_ash Magnesium Total_phenols Flavanoids Nonflavanoid_phenols Proanthocyanins Color_intensity Hue OD280/OD315_diluted wines Proline
2 1.514340767 -0.560668221 0.23139979 -1.166303174 1.908521507 0.806721729 1.031908069 -0.657707799 1.221438453 0.251008784 0.361158491 1.84272147
3 0.245596828 -0.498008556 -0.825667215 -2.483840525 0.01809398 0.567048088 0.731565283 -0.818410597 -0.543188717 -0.292496232 0.404908465 1.110317231
4 0.196325219 0.021171524 1.106213863 -0.267982252 0.088109814 0.806721729 1.212113741 -0.497005002 2.129959372 0.268262912 0.317408517 0.786369202
5 1.6867914 -0.345835084 0.486553895 -0.806974805 0.928299826 2.484437221 1.462399395 -0.979113395 1.029251335 1.182731669 -0.426341036 1.180740715
6 0.294868437 0.22705328 1.835225591 0.450674485 1.278378998 0.806721729 0.6614853 0.226157589 0.400275314 -0.318377423 0.361158491 0.448336476
7 1.47738706 -0.515911317 0.304300963 -1.286079296 0.858283992 1.55769914 1.362285134 -0.175599406 0.662348656 0.729810822 0.404908465 0.335658901
8 1.711427204 -0.41744613 0.304300963 -1.465743481 -0.261969358 0.327374446 0.491291055 -0.497005002 0.679820212 0.082781041 0.273658544 1.363841775
9 1.304936428 -0.16680747 0.887510345 -0.567422559 1.488426501 0.487156874 0.481279629 -0.416653603 -0.595603386 -0.003489596 0.448658438 1.363841775
10 2.253414907 -0.623327885 -0.716315456 -1.645407665 -0.191953523 0.806721729 0.95181666 -0.577356401 0.679820212 0.061213382 0.536158386 0.335658901
11 1.058578381 -0.882917925 -0.351809592 -1.046527051 -0.121937689 1.094330099 1.122010905 -1.139816193 0.452689983 0.93254682 0.22990857 1.321587684
12 1.354208037 -0.15785609 -0.242457833 -0.447646437 0.368173151 1.046395371 1.29220515 -1.139816193 1.378682458 0.298457635 1.279907939 0.786369202
13 1.378843842 -0.766549976 -0.16955666 -0.806974805 -0.331985192 -0.151972837 0.401188219 -0.818410597 -0.036513589 -0.025057256 0.929908149 0.29340481
14 0.923081456 -0.542765459 0.158498617 -1.046527051 -0.752080198 0.487156874 0.731565283 -0.577356401 0.382803758 0.233754657 0.842408202 0.406082385
15 2.154871688 -0.542765459 0.085597444 -2.423952463 -0.61204853 1.286069013 1.662627919 0.547563185 2.129959372 0.147484019 1.279907939 0.166642538
16 1.699109302 -0.41744613 0.049146858 -2.244288279 0.158125648 1.605633868 1.612570788 -0.577356401 2.392032714 1.053325713 1.061158071 0.546929354
17 0.775266628 -0.471154414 1.215565622 -0.687198682 0.858283992 0.886612943 0.881736676 -0.497005002 -0.228700707 0.967055075 1.41115786 0.377912991
18 1.600566084 -0.372689226 1.288466795 0.151234178 1.418410667 0.806721729 1.111999479 -0.255950805 0.662348656 0.492566569 0.492408412 0.053964962
19 1.021624674 -0.68598755 0.923960931 0.151234178 1.068331495 1.046395371 1.37229656 0.306508988 0.225559753 0.665107844 0.754908255 -0.058712613
20 1.465069158 -0.668084789 0.413652722 -0.896806897 0.578220655 1.605633868 1.902902148 -0.336302204 0.470161539 1.570949537 1.192407992 0.29340481
21 0.78758453 0.683573695 0.705257413 -1.286079296 1.138347329 0.646939302 1.001873791 -1.541573188 0.120730416 0.018078063 0.011158701 1.053978443
22 1.304936428 -0.632279266 -0.315359006 -1.046527051 1.838505673 1.126286585 1.142033757 -0.979113395 0.889478886 0.255322316 0.57990836 1.546942835
23 -0.086986535 1.310170343 1.03331269 -0.267982252 0.158125648 0.183570261 0.381165367 -0.898761996 0.679820212 -0.240733849 0.317408517 1.279333594
24 0.873809846 -0.42639751 -0.023754315 -0.866862867 0.088109814 0.503135117 0.851702398 -0.738059198 0.173145084 -0.542681081 0.667408307 1.955399046
25 -0.185529754 -0.659133408 0.559455067 -0.507534498 -0.331985192 0.295417961 0.341119662 -0.818410597 -0.228700707 -0.486605166 0.57990836 1.43426526
26 0.615133898 -0.471154414 0.887510345 0.151234178 -0.261969358 0.375309174 0.581393891 -0.657707799 0.120730416 -0.663459973 0.711158281 1.701874501
27 0.060828293 -0.256321277 3.110996114 1.648435713 1.698474004 0.535091602 0.651473874 0.868968781 0.574990876 -0.637578782 0.754908255 0.828623293
28 0.479636972 -0.506959936 0.923960931 -1.01658302 -0.472016861 0.886612943 0.911770955 -0.175599406 -0.246172263 -0.111327893 -0.163841194 0.856792686
29 0.368775851 -0.55171684 -0.825667215 -0.747086744 -0.402001026 0.167592018 0.160913991 -0.738059198 -0.420887824 -0.477978102 0.273658544 0.222981325
30 1.070896284 -0.390591988 1.580071486 -0.028430007 0.50820482 1.046395371 0.941805234 0.065454791 0.295445977 -0.240733849 1.279907939 1.110317231
31 1.255664818 -0.587522363 -0.57051311 -1.046527051 -0.261969358 0.567048088 0.301073957 -0.818410597 0.679820212 -0.154463212 0.361158491 1.377926472
32 0.898445651 -0.748647215 1.215565622 0.899834945 0.088109814 1.126286585 1.222125167 -0.577356401 1.378682458 0.276889975 1.017408097 0.138473144
33 0.713677116 -0.605425124 -0.023754315 -0.118262099 0.438188986 0.902591186 1.16205661 -1.139816193 0.627405544 0.7945138 0.57990836 0.377912991
34 0.836856139 -0.453251652 -0.023754315 -0.687198682 0.298157317 0.199548504 0.6614853 0.467211786 0.662348656 -0.525426953 1.192407992 0.363828294
35 0.935399358 -0.721793073 1.215565622 0.001514024 2.258600679 1.046395371 0.711542431 1.110022978 -0.420887824 0.147484019 1.279907939 0.546929354
36 0.6274518 -0.480105794 1.03331269 -0.14820613 0.718252323 0.087700804 0.501302481 -0.577356401 -0.088928258 -0.370139806 0.623658333 0.363828294
37 0.590498093 -0.471154414 0.158498617 0.300954331 0.01809398 0.646939302 0.95181666 -0.818410597 0.470161539 0.018078063 0.361158491 1.208910109
38 0.344140046 -0.623327885 1.725873832 -1.196247204 0.718252323 0.487156874 0.651473874 -0.175599406 -0.403416268 -0.197598531 0.57990836 0.237066022
39 0.060828293 -0.614376505 0.668806826 -0.447646437 -0.121937689 0.247483232 0.401188219 -0.577356401 -0.263643819 -0.348572146 0.711158281 -0.143220794
40 0.085464098 -0.748647215 -0.971469561 -1.196247204 -0.121937689 0.167592018 0.611428169 -0.657707799 -0.385944712 -0.585816399 0.973658123 0.11030375
41 1.502022865 1.480246576 0.523004481 -1.884959911 1.978537342 1.126286585 1.011885217 -1.300518991 0.854535774 0.018078063 -0.295091115 1.293418291
42 0.689041312 -0.560668221 -0.206007247 -0.986638989 1.208363164 1.365960227 1.262170872 -0.175599406 1.308796233 0.462371846 -0.032591273 1.082147837
43 0.504272777 1.345975865 -0.898568388 -0.208094191 -0.682064364 0.247483232 0.651473874 -0.738059198 -0.193757594 -0.335631551 -0.207591167 0.546929354
44 1.083214186 -0.399543368 0.814609172 -1.345967358 0.088109814 1.525742654 1.532479379 -1.541573188 0.190616641 0.160424615 -0.338841089 1.335672381
45 0.294868437 1.471295195 -0.278908419 -0.59736659 0.228141483 0.551069845 0.601416743 -0.336302204 0.120730416 -0.301123296 -0.601340931 0.546929354
46 0.060828293 -0.506959936 -0.971469561 -0.747086744 0.50820482 1.126286585 0.971839512 -0.657707799 0.767177993 -0.007803128 -0.338841089 1.039893746
47 1.489704963 1.525003479 0.267850376 -0.17815016 0.788268158 0.886612943 0.621439595 -0.497005002 -0.595603386 0.078467509 -0.382591062 1.011724352
48 1.699109302 1.122191348 -0.315359006 -1.046527051 0.158125648 1.525742654 1.142033757 -0.738059198 1.046722891 -0.068192574 0.361158491 1.166656018
49 1.107849991 -0.587522363 -0.898568388 -1.046527051 0.088109814 1.286069013 1.362285134 -1.220167592 0.959365111 0.44943125 -0.207591167 1.011724352
50 1.354208037 -0.283175419 0.122048031 -0.208094191 0.228141483 0.726830515 0.891748103 -0.336302204 1.378682458 0.492566569 0.492408412 0.194811931
51 1.1571216 -0.542765459 -0.351809592 -0.627310621 0.578220655 0.934547672 1.512456526 -0.336302204 0.854535774 1.657220175 0.711158281 0.687776323
52 0.060828293 -0.542765459 -1.190173079 -2.124512156 -0.542032695 0.678895787 1.242148019 -1.541573188 2.304674933 0.923919756 0.711158281 0.420167082
53 1.021624674 -0.614376505 0.851059758 -0.687198682 -0.402001026 0.247483232 0.961828086 -1.139816193 1.221438453 0.233754657 1.236157966 1.06806314
54 1.009306772 -0.524862698 0.194949204 -1.645407665 0.788268158 2.532371949 1.71268505 -0.336302204 0.487633095 0.859216778 0.22990857 0.913131474
55 0.94771726 -0.390591988 1.142664449 -0.717142713 1.068331495 1.126286585 0.761599562 0.226157589 0.155673528 0.535701888 0.754908255 0.448336476
56 0.910763553 -0.596473743 -0.424710765 -0.926750928 1.278378998 0.487156874 0.87172525 -1.220167592 0.050844191 0.341592953 -0.163841194 0.828623293
57 0.689041312 -0.542765459 0.340751549 0.300954331 1.138347329 1.062373614 0.751588136 -1.300518991 1.500983351 0.514134228 0.098658649 0.589183445
58 1.502022865 -0.569619601 -0.242457833 -0.956694959 1.278378998 1.44585144 0.971839512 -0.818410597 0.767177993 0.570210143 -0.076341246 0.983554959
59 0.356457949 -0.327932323 1.142664449 -0.806974805 0.158125648 1.126286585 1.202102314 -0.416653603 0.120730416 0.406295932 0.492408412 0.321574204
60 0.886127749 -0.81130688 0.486553895 -0.836918836 0.578220655 1.765416296 1.642605067 -1.38087039 0.784649549 0.751378481 -0.295091115 0.363828294
61 -0.776789065 -1.249924533 -3.668812953 -2.663504709 -0.822096033 -0.503494178 -1.460937052 -0.657707799 -2.045742545 -1.340684477 0.404908465 -1.115064881
62 -0.826060674 -1.106702442 -0.315359006 -1.046527051 0.088109814 -0.391646479 -0.94034289 2.154591165 -2.063214101 -0.77129827 1.279907939 -1.326335335
63 -0.444205702 -0.873966544 -1.263074252 -0.806974805 0.01809398 -0.439581207 -0.619977252 1.351077175 -1.696311422 0.298457635 0.098658649 -1.43901291
64 0.824538237 -0.972431732 -1.627580115 -0.447646437 -0.402001026 -0.311755265 -0.239543057 -0.336302204 -1.504124305 -0.542681081 1.192407992 -0.213644279
65 -0.776789065 -1.0798483 -0.752766042 -0.14820613 -0.892111867 1.925198724 1.071953774 -1.38087039 0.487633095 -0.262301509 1.148658018 0.363828294
66 -1.023147112 -0.793404118 0.595905654 -0.14820613 0.298157317 -0.647298363 -0.279588762 0.708265983 -0.979977621 -0.90933129 2.154907414 -0.537592308
67 -0.776789065 -1.008237255 0.705257413 -0.417702406 -0.121937689 0.199548504 0.621439595 0.065454791 0.854535774 -0.197598531 1.017408097 -0.43899943
68 0.134735707 -1.187264868 -2.429493016 -1.345967358 -1.522254376 1.094330099 1.152045184 -0.818410597 1.203966897 0.1043487 0.711158281 0.800453899
69 -0.776789065 -1.044042777 -1.627580115 0.031458055 -1.522254376 -0.295777022 -0.029303107 -0.738059198 -0.962506065 -0.163090276 0.711158281 1.222994806
70 0.41804746 -1.249924533 -0.023754315 -0.747086744 0.718252323 0.375309174 -0.73010294 1.511779973 -2.045742545 -0.814433589 0.273658544 -0.960133215
71 -0.973875502 -1.026140016 -2.247240084 -0.806974805 3.588901532 -0.711211334 -0.750125793 -1.782627385 1.588341132 -0.952466609 1.41115786 0.645522233
72 -0.875332284 -0.650182027 -0.57051311 0.2710103 0.228141483 -1.909579543 -1.010422874 0.065454791 -0.228700707 -0.866195971 -0.225091157 -1.115064881
73 1.058578381 -0.739695834 1.106213863 1.648435713 -0.962127701 1.046395371 0.831679545 -1.220167592 0.487633095 -0.723849419 1.76115765 0.772284505
74 0.602815995 -0.605425124 -0.461161351 1.348995406 -0.892111867 -0.663276606 -0.189485926 -0.738059198 -0.979977621 -0.568562272 0.098658649 0.237066022
75 -0.013079121 -0.596473743 0.851059758 3.145637249 2.74871152 1.605633868 0.861713824 -1.220167592 0.6448771 -0.736790015 1.542407782 1.2511642
76 -1.28182306 -1.115653823 -0.242457833 0.450674485 0.088109814 1.73345981 0.11085686 -1.862978784 0.10325886 -0.797179461 0.142408622 0.730030414
77 -1.65136013 -0.408494749 -1.627580115 -1.046527051 -0.191953523 -1.094689161 -0.459794433 -0.175599406 -0.770318947 -0.542681081 1.192407992 -0.66435458
78 0.036192488 -1.285730056 -2.393042429 -1.046527051 -0.962127701 -0.551428907 0.000731172 -0.979113395 -0.228700707 -0.197598531 1.017408097 -0.185474885
79 -1.429637888 0.4955947 -0.497611938 -0.447646437 0.858283992 -0.91892849 -0.710080088 0.547563185 -1.11975007 -1.038737246 0.011158701 -0.129136098
80 -0.826060674 -1.20516763 -1.518228356 -1.405855419 2.538664016 -0.63132012 -0.1794745 -0.095248007 2.042601591 -0.715222356 0.448658438 -0.424914733
81 -0.370298288 1.372830007 0.122048031 1.049555099 0.088109814 0.854656458 0.521325333 0.547563185 0.627405544 -1.073245501 1.017408097 0.730030414
82 -1.232551451 -1.267827295 -1.335975424 -0.14820613 -0.962127701 0.199548504 0.230993974 -0.497005002 -0.281115375 -1.103440224 1.848657598 0.715945717
83 -0.345662484 -0.471154414 -0.606963697 -0.208094191 -0.962127701 -0.151972837 0.501302481 -0.818410597 0.312917534 -0.499545762 0.886158176 0.744115111
84 -1.134008233 -1.0798483 0.523004481 1.348995406 -1.522254376 -0.471537693 -0.449783007 0.306508988 -0.333530044 -1.23284618 1.542407782 0.152557841
85 0.060828293 1.363878627 -0.16955666 0.899834945 -1.032143536 -1.03077619 -0.439771581 1.993888367 0.050844191 -0.111327893 -0.513840984 -0.84745564
86 -1.429637888 -1.294681437 0.778158586 -0.447646437 -0.402001026 -0.151972837 0.180936843 -1.139816193 1.326267789 -0.866195971 -0.732590852 0.65960693
87 -0.407251995 -1.21411901 -0.461161351 -0.447646437 -0.051921855 -0.151972837 -0.089371664 -0.497005002 -0.228700707 -1.051677842 1.192407992 0.772284505
88 -1.035465014 -0.650182027 -0.206007247 0.989667037 -0.682064364 -0.823059034 -0.339657319 0.547563185 -0.053985145 -1.125007884 1.629907729 -0.495338217
89 -1.663678033 -0.596473743 0.923960931 1.94787602 -0.822096033 -0.599363635 -0.419748728 0.306508988 -0.43835938 -1.060304905 1.76115765 0.842707989
90 -1.675995935 -0.247369897 0.340751549 0.630338669 -1.10215937 -0.551428907 -0.339657319 0.94932018 -0.420887824 -0.974034268 0.186158596 0.194811931
91 -1.134008233 -0.900820687 -0.242457833 1.229219283 -2.082381051 -0.151972837 -0.439771581 0.467211786 -0.368473156 -1.431268647 0.492408412 0.842707989
92 -1.134008233 -0.453251652 -0.16955666 -0.297926283 -1.312206873 -1.110667404 -0.529874417 1.270725776 0.085787304 -1.146575543 0.536158386 -0.48125352
93 -1.232551451 -0.739695834 0.194949204 0.750114792 -0.962127701 -1.350341045 -0.780160071 1.110022978 0.068315748 -0.628951718 0.404908465 0.053964962
94 -0.382616191 -0.721793073 -0.388260179 0.360842393 -1.382222707 -1.462188745 -0.569920121 1.75283417 0.050844191 -0.866195971 0.011158701 -0.777032156
95 -0.875332284 0.441886416 -0.534062524 -0.447646437 -0.822096033 0.247483232 0.220982548 -0.898761996 0.697291769 -1.25441384 0.842408202 0.969470262
96 -1.70063174 -0.310029561 -0.315359006 -0.447646437 -0.121937689 1.15824307 0.230993974 -1.541573188 -0.420887824 -0.779925334 0.886158176 0.490590567
97 -0.653610042 -0.730744454 -0.606963697 -0.14820613 4.35907571 0.327374446 0.2410054 -0.336302204 2.95112251 -1.060304905 0.886158176 0.025795569
98 -1.466591595 -0.193661612 1.361367968 0.600394638 2.398632348 -1.110667404 -1.040457152 -1.782627385 -0.053985145 -1.103440224 -0.032591273 -0.495338217
99 -0.875332284 -0.829209641 -1.408876597 -1.046527051 -1.032143536 0.40726566 0.471268203 -0.577356401 0.312917534 -0.930898949 1.192407992 0.180727235
100 -0.776789065 -1.133556584 -0.971469561 -0.297926283 -0.822096033 1.957155209 1.722696476 -0.979113395 0.627405544 -0.240733849 0.361158491 0.222981325
101 -0.875332284 0.746233359 -0.57051311 -0.447646437 -0.822096033 0.886612943 0.961828086 0.708265983 2.129959372 -1.189710862 2.023657493 0.307489507
102 -1.134008233 -0.229467135 -2.429493016 -0.59736659 -0.191953523 -0.104038109 0.140891138 -0.818410597 -0.333530044 -0.758357674 1.367407887 0.490590567
103 -0.493477312 -0.891869306 -1.700481288 -0.297926283 -0.822096033 -1.350341045 -0.670034383 -0.577356401 -0.420887824 -1.125007884 0.361158491 0.222981325
104 -0.813742772 0.10173395 0.340751549 0.450674485 -0.121937689 0.423243903 0.080822581 -0.175599406 -0.490774049 -0.974034268 -0.688840878 1.082147837
105 -1.454273693 -0.55171684 -1.773382461 0.001514024 -0.962127701 0.327374446 -0.38971445 0.065454791 -0.298586931 -1.293235627 -0.076341246 -0.241813673
106 -0.604338433 -0.542765459 -1.408876597 0.300954331 -1.032143536 -0.151972837 -0.109394517 -0.336302204 -0.193757594 -0.913644822 0.361158491 1.349757078
107 -0.715199554 0.191247757 -0.351809592 0.750114792 -0.682064364 -0.982841462 -0.189485926 2.395645362 -0.298586931 -1.017169587 -0.426341036 0.969470262
108 -0.924603893 -0.542765459 -0.898568388 -0.14820613 -1.382222707 -1.03077619 0.000731172 0.065454791 0.068315748 -0.715222356 0.186158596 0.786369202
109 -0.345662484 -0.524862698 -0.315359006 0.899834945 -1.10215937 -1.462188745 -0.269577336 0.94932018 0.068315748 -0.758357674 -0.338841089 -0.269983067
110 -0.9615576 -0.936626209 -1.554678943 -0.14820613 -0.542032695 0.103679047 0.010742598 0.226157589 0.854535774 -1.017169587 -0.426341036 0.575098748
111 -1.712949642 -0.882917925 1.215565622 0.151234178 -0.402001026 0.710852273 0.891748103 -0.577356401 1.570869575 -1.038737246 0.011158701 0.913131474
112 -1.897718177 1.256462058 -1.992085979 0.001514024 0.50820482 1.413894955 0.551359612 -0.979113395 3.475269194 -0.930898949 -0.907590747 0.279320113
113 -0.59202053 0.083831189 -0.716315456 0.450674485 -0.822096033 0.40726566 0.2410054 -0.818410597 -0.648018054 -1.319116818 -0.251341141 0.237066022
114 -1.528181107 0.307615706 2.017478523 0.151234178 0.228141483 -0.870993762 0.000731172 1.913536968 -0.945034508 -0.542681081 1.192407992 -0.157305491
115 -1.959307688 -1.428952147 0.486553895 0.450674485 -0.822096033 0.295417961 -0.019291681 0.467211786 -0.263643819 -0.853255375 0.623658333 -0.424914733
116 -1.134008233 -0.847112402 0.486553895 0.899834945 -1.10215937 0.423243903 0.261028253 0.547563185 -0.962506065 -0.930898949 -0.12009122 0.814538596
117 -2.427387977 -0.739695834 -0.606963697 0.600394638 -1.032143536 0.263461475 0.140891138 1.270725776 0.732234881 -1.362252137 3.292406731 0.363828294
118 -1.454273693 -0.775501357 -1.372426011 0.390786423 -0.962127701 -0.503494178 -0.429760155 -0.497005002 -0.106399814 -1.340684477 -0.032591273 1.011724352
119 -0.715199554 -0.650182027 -0.643414283 0.899834945 0.578220655 -0.471537693 0.060799729 -0.175599406 0.033372635 -1.293235627 0.448658438 0.490590567
120 -0.284072972 0.978969257 -1.408876597 -1.046527051 -1.382222707 -1.062732675 -0.780160071 0.547563185 -1.329408743 -0.715222356 -1.126340616 -0.692523974
121 -1.232551451 0.978969257 -1.335975424 -0.14820613 -0.892111867 -0.471537693 -0.38971445 0.065454791 0.487633095 -1.629691113 -0.12009122 0.617352839
122 -1.910036079 0.056977047 0.194949204 0.151234178 -0.261969358 0.966504157 0.761599562 -0.336302204 0.41774687 -0.779925334 -0.688840878 1.096232534
123 -1.774539153 -0.256321277 3.1474467 2.696476788 1.348394832 1.413894955 3.05421616 0.868968781 0.487633095 0.406295932 -0.12009122 1.518773441
124 -0.715199554 1.874107326 1.324917381 2.097596174 0.158125648 -0.151972837 0.100845433 0.547563185 0.208088197 -1.284608563 -0.163841194 0.715945717
125 0.060828293 3.100446479 -0.862117801 0.600394638 -0.962127701 0.519113359 0.621439595 -0.497005002 0.732234881 -1.060304905 -0.995090695 0.687776323
126 -1.392684181 1.766690757 0.085597444 0.450674485 -1.242191039 0.902591186 1.001873791 -1.220167592 2.304674933 -0.974034268 -0.907590747 1.448349957
127 -1.146326135 -0.15785609 -0.716315456 0.450674485 -1.032143536 0.487156874 0.621439595 0.065454791 -0.420887824 -0.991288395 -0.426341036 0.941300868
128 -0.702881651 -0.721793073 -0.278908419 0.600394638 -0.962127701 0.710852273 1.122010905 0.226157589 0.312917534 -0.482291634 -1.170090589 0.321574204
129 -1.4912274 -0.184710232 1.507170313 2.696476788 -0.542032695 -0.263820537 0.210971122 1.75283417 0.295445977 -0.88776363 0.054908675 -0.241813673
130 -0.776789065 -0.632279266 -0.242457833 1.498715559 -0.822096033 -0.120016352 0.421211072 0.306508988 0.540047763 -1.267354435 -0.295091115 0.237066022
131 -1.183279842 1.757739377 0.049146858 0.750114792 -1.382222707 -0.311755265 -0.279588762 0.467211786 -0.420887824 -1.060304905 -0.732590852 -0.058712613
132 -0.173211851 -0.882917925 -0.16955666 -0.447646437 1.558442335 -1.254471589 -0.780160071 -1.220167592 -1.137221626 -0.413275124 -0.863840773 -1.861553818
133 -0.148576047 0.585108507 0.122048031 0.151234178 0.298157317 -1.590014687 -0.81019435 -0.979113395 -1.329408743 0.147484019 -0.951340721 -1.678452758
134 -0.234801363 -0.023585379 0.122048031 1.348995406 -0.121937689 -1.829688329 -0.94034289 -0.738059198 -1.329408743 0.276889975 -1.301340511 -1.762960939
135 -0.370298288 1.086385825 -0.023754315 0.600394638 0.438188986 -0.950884976 -0.830217202 -1.541573188 -1.311937187 -0.025057256 -0.776340826 -1.861553818
136 -0.604338433 -0.981383113 -0.424710765 -0.59736659 -1.032143536 -0.471537693 -1.450925626 1.913536968 -0.595603386 0.169051679 -0.907590747 -1.551690486
137 -0.493477312 0.110685331 -0.606963697 -0.297926283 -0.402001026 -1.078710918 -1.370834217 2.154591165 -1.137221626 0.880784438 -0.995090695 -1.453097607
138 -0.924603893 2.133697366 0.63235624 0.450674485 -0.752080198 -1.462188745 -1.561051314 1.351077175 -1.381823412 -0.521113421 -0.907590747 -1.889723212
139 -0.579702628 2.84085644 0.996862104 1.648435713 -0.261969358 -0.807080791 -1.430902774 2.154591165 -0.857676728 -0.025057256 -0.601340931 -1.298165941
140 0.602815995 1.122191348 -0.643414283 0.001514024 -0.822096033 -1.078710918 -1.551039888 1.75283417 -1.242050963 0.276889975 -0.645090905 -1.115064881
141 -0.197847656 0.558254365 0.887510345 1.348995406 0.088109814 0.039766076 -1.430902774 1.351077175 -1.364351856 -0.059565511 -0.295091115 -0.650269883
142 -0.086986535 0.423983655 1.215565622 0.450674485 -0.261969358 -1.20653686 -1.531017036 1.351077175 -1.469181193 -0.197598531 -0.8200908 -0.424914733
143 0.442683265 0.200199138 -0.060204901 0.151234178 -0.752080198 -1.430232259 -1.531017036 0.065454791 -1.66136831 0.233754657 -1.126340616 -0.199559582
144 0.639769702 0.746233359 1.288466795 1.199275252 -0.191953523 -1.190558618 -1.510994183 1.110022978 -1.818612315 -0.305436828 -0.295091115 -0.777032156
145 0.762948725 2.339579121 -0.060204901 0.151234178 -0.542032695 -0.471537693 -1.23067425 0.868968781 -0.997449177 -0.283869168 -0.207591167 -0.791116852
146 -0.924603893 1.381781388 -0.606963697 -0.297926283 0.858283992 -1.462188745 -1.250697102 -0.577356401 -0.787790503 1.359586476 -1.345090484 -0.861540337
147 0.196325219 1.104288587 -0.789216629 0.450674485 0.158125648 -1.270449832 -1.480959905 0.547563185 -0.508245605 -0.456410443 -1.563840353 -1.312250638
148 1.083214186 2.420141547 -0.497611938 0.151234178 -1.382222707 -2.101318456 -1.691199855 0.306508988 -1.591482085 -0.068192574 -1.6513403 -1.80521503
149 -0.160893949 2.035232178 0.413652722 0.600394638 -0.962127701 -0.950884976 -1.380845643 0.868968781 -1.276994075 1.118028691 -1.826340195 -1.058726094
150 0.393411656 0.808893024 0.049146858 0.600394638 -0.542032695 -0.583385392 -1.270719955 0.708265983 -0.595603386 1.450170645 -1.782590222 -1.39675882
151 0.097782 1.399684149 -0.023754315 0.600394638 0.928299826 -1.414254017 -0.640000105 -0.175599406 -0.787790503 1.872896769 -1.695090274 -1.80521503
152 0.615133898 0.701476456 0.923960931 1.348995406 1.62845817 -1.430232259 -0.459794433 -1.139816193 -0.595603386 1.527814219 -1.607590327 -1.847469121
153 -0.259437168 0.298664325 0.413652722 0.750114792 0.858283992 -1.302406317 -0.670034383 -0.979113395 -0.578131829 2.476791231 -2.088840038 -1.608029273
154 0.134735707 -0.390591988 1.397818554 1.798155867 1.138347329 -0.151972837 -0.750125793 -0.818410597 -0.053985145 0.880784438 -1.520090379 -1.80521503
155 0.282550535 0.862601308 -0.315359006 -0.297926283 -0.121937689 -0.791102548 -1.200639971 1.993888367 0.487633095 2.356012338 -1.738840248 -1.551690486
156 -0.518113116 -0.936626209 -0.971469561 0.151234178 0.228141483 -1.302406317 -1.450925626 1.351077175 -0.333530044 1.096461031 -1.6513403 -1.495351698
157 0.208643121 2.554412258 -0.16955666 0.750114792 -0.472016861 -0.886972005 -1.400868495 1.993888367 -0.071456702 1.225866988 -1.563840353 -1.593944576
158 1.033942577 1.596614524 0.049146858 0.001514024 -0.752080198 -0.791102548 -1.200639971 0.94932018 -0.053985145 1.704669026 -1.695090274 -1.368589426
159 -0.678245847 0.62091403 0.996862104 2.247316327 -0.191953523 -0.63132012 -1.450925626 2.154591165 -0.787790503 1.053325713 -1.257590537 -1.241827154
160 1.649837693 -0.587522363 1.215565622 1.648435713 -0.121937689 0.806721729 -0.720091514 1.351077175 1.937772254 3.425768243 -1.695090274 -0.917879125
161 0.590498093 -0.596473743 0.996862104 0.899834945 -0.752080198 0.487156874 -0.930331464 1.270725776 1.221438453 2.886576759 -1.695090274 -1.171403669
162 -0.789106967 1.337024485 0.049146858 0.450674485 -0.822096033 0.007809591 -1.110537136 1.110022978 -0.962506065 1.118028691 -1.738840248 -1.453097607
163 0.849174042 0.826795786 0.63235624 0.151234178 0.50820482 -0.74316782 -1.470948478 1.110022978 -1.381823412 0.354533549 0.011158701 -1.115064881
164 -0.185529754 0.835747166 0.778158586 0.750114792 0.438188986 -1.03077619 -1.430902774 1.913536968 -1.102278514 0.225127593 -0.382591062 -0.706608671
165 -0.050032828 0.996872019 -0.060204901 -0.297926283 0.438188986 -1.446210502 -1.330788512 0.306508988 -1.137221626 0.095721637 -1.213840563 -1.21365776
166 0.960035163 0.379226751 -0.242457833 0.750114792 -0.682064364 -1.510123473 -1.350811364 0.386860387 -0.979977621 1.950540342 -1.126340616 -1.312250638
167 0.898445651 1.811447661 -0.388260179 0.899834945 -0.822096033 -1.621971173 -1.561051314 1.270725776 -0.770318947 0.673734908 -0.776340826 -1.21365776
168 0.553544386 1.220656536 0.851059758 1.049555099 0.788268158 -0.950884976 -1.110537136 0.547563185 -0.228700707 2.425028848 -0.47009101 -1.481267001
169 -0.222483461 0.925260973 -0.242457833 0.001514024 -0.822096033 -1.302406317 -1.370834217 0.306508988 -1.084806957 2.24386051 -1.038840668 -1.21365776
170 0.713677116 0.218101899 1.179115036 1.498715559 0.368173151 -1.190558618 -1.190628545 0.226157589 -0.088928258 1.55369541 -0.951340721 -1.143234275
171 0.491954874 2.026280797 1.798775004 1.648435713 0.858283992 -0.503494178 -1.070491431 -0.738059198 -0.840205172 1.4846789 -1.257590537 -0.974217912
172 -0.986193405 0.62091403 -0.16955666 -0.14820613 -0.261969358 -1.669905901 -1.541028462 0.306508988 -1.504124305 0.190619338 -1.301340511 -1.100980185
173 -0.284072972 0.048025666 -0.315359006 0.001514024 -0.962127701 -1.446210502 -1.521005609 0.94932018 -1.66136831 2.088572931 -1.695090274 -1.382674123
174 1.428115451 0.155442234 0.413652722 0.151234178 -0.61204853 -0.982841462 -1.330788512 0.627914584 -0.613074942 2.002302725 -1.476340406 -1.269996547
175 0.873809846 2.966175769 0.304300963 0.300954331 -0.331985192 -0.982841462 -1.420891348 1.270725776 -0.927562952 1.13959635 -1.388840458 -1.227742457
176 0.491954874 1.40863553 0.413652722 1.049555099 0.158125648 -0.791102548 -1.280731381 0.547563185 -0.316058487 0.967055075 -1.126340616 -1.481267001
177 0.331822144 1.739836615 -0.388260179 0.151234178 1.418410667 -1.126645647 -1.340799938 0.547563185 -0.420887824 2.217979318 -1.607590327 -1.481267001
178 0.208643121 0.22705328 0.012696272 0.151234178 1.418410667 -1.03077619 -1.350811364 1.351077175 -0.228700707 1.82976145 -1.563840353 -1.39675882
179 1.391161744 1.578711763 1.361367968 1.498715559 -0.261969358 -0.391646479 -1.270719955 1.592131372 -0.420887824 1.786626131 -1.520090379 -1.424928213

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#填写答案时请删除掉下划线
_______(rpart) #加载rpart包(2分)
_________(201) #设置种子数为201 (2分)
train=__________(1:nrow(iris),0.75*nrow(iris)) #对iris数据集抽样75% (2分)
tdata=iris[train,] #设置训练集
vdata=iris[_______,] #剩下的25%作为测试集 (2分)
tree=________(tdata$Species~.,data=tdata,method="class",parms=list(split="information"))#建立决策树，请填写正确的函数名 (2分)
print(tree)#查看决策树
cat("根节点是","_______") #根据查看的结果，将根节点属性的名称填写在下划线中 (2分)
pred_tree=________(tree,newdata=vdata,type="class") #用决策树对测试集进行预测 (2分)
conf_tree=_______(vdata$Species,pred_tree,dnn=c("真实值","预测值")) #生成混淆矩阵 (2分)
sum(_______(conf_tree))/sum(conf_tree) #在下划线出填写合适的函数名，使得公式能够计算准确率 (2分)
cat("预测准确率为",____________) #在下划线处填写准确率数值，按程序实际运行填写，不要四舍五入 (2分)

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_______("longley.rdata") #读取longley.rdata数据集 (2分)
longley=________(longley,select=-Year) #删除掉Year属性 (2分)
cat("删除后，此时数据框还剩",___,"列")#填写剩余的列数(2分)
longley=as.data.frame(_______(longley))#对数据进行z-score规范化(2分)
md=lm(__________,data=longley)#以GNP.deflator为因变量，建立它与其他所有变量之间的多元线性回归模型(4分)
_______(md)#显示模型结果 (2分)
cat("查看模型结果，此模型的拟合度","______")#填 好/不好(2分)
md_best=step(md)#对模型进行逐步法筛选出最优回归方程(2分)
cat("最优模型删除了",______,"个变量") #根据生成的结果填写删除的变量数量(2分)
new=_______(GNP=-1.3,Unemployed=-0.9,Armed.Forces=-1.45, Population=-1.46, Employed=-1.4) #填写合适的函数，生成一条新数据 (2分)
predict(md_best,new)
cat("预测的GNP.deflator结果是",_______) #将预测的数值结果填写在下划线处，按程序运行结果填写不要四舍五入。(2分)

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test/t-code/2720048/R1007.R Normal file
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iris=______("iris.csv") #读取iris.csv文件 (2分)
iris=_______(iris) #填写合适的函数名，删除缺失值 (2分)
iris=scale(iris)
d=______(iris) #填写合适的函数名，计算距离矩阵 (2分)
hc=_________(d,method="ave") #填写合适的函数名，采用平均距离对数据进行层次聚类 (2分)
cutree(hc,k=2) #将数据分成2类
cat("根据分类结果，第6个和66个样本是否被分在同一类？","______") #填 是/否 (2分)

151
test/t-code/2720048/iris.csv Normal file
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,Sepal.Length,Sepal.Width,Petal.Length,Petal.Width
1,6.2,2.8,4.8,1.8
2,6.2,2.2,4.5,1.5
3,6.7,3.3,5.7,2.1
4,4.9,2.5,4.5,1.7
5,6.7,2.5,5.8,1.8
6,5.3,3.7,1.5,0.2
7,6.3,2.5,4.9,1.5
8,6.1,2.8,4.7,1.2
9,6,2.2,5,1.5
10,6.8,2.8,4.8,1.4
11,5.5,4.2,1.4,0.2
12,5,3.2,1.2,0.2
13,NA,2.7,4.2,1.3
14,6.8,3,5.5,2.1
15,4.6,3.2,1.4,0.2
16,6.1,3,4.9,1.8
17,5,3.5,1.6,0.6
18,6.9,3.1,4.9,1.5
19,7.2,3,5.8,1.6
20,4.8,3,1.4,0.3
21,6.4,3.2,5.3,2.3
22,5.6,3,4.1,1.3
23,4.9,3.1,1.5,0.1
24,4.4,3,1.3,0.2
25,5.4,3.7,1.5,0.2
26,4.9,3.1,1.5,0.2
27,6,NA,4,1
28,6.7,3,5,1.7
29,7.3,2.9,6.3,1.8
30,6.6,2.9,4.6,1.3
31,4.4,3.2,1.3,0.2
32,5.6,2.5,3.9,1.1
33,6.1,2.8,4,1.3
34,5.7,2.8,4.5,1.3
35,5.5,3.5,1.3,0.2
36,5.5,2.6,4.4,1.2
37,5,3.5,1.3,0.3
38,5.6,3,4.5,1.5
39,5.1,3.8,1.6,0.2
40,5.8,2.6,4,1.2
41,5.1,3.5,1.4,0.2
42,6.5,3.2,5.1,2
43,4.6,3.1,1.5,0.2
44,6.4,2.9,4.3,1.3
45,5,3.3,1.4,0.2
46,5.9,3,5.1,1.8
47,5.8,4,1.2,0.2
48,5.8,2.7,3.9,1.2
49,6.3,2.7,4.9,1.8
50,7.7,3,6.1,2.3
51,6.7,3,5.2,2.3
52,5.5,2.3,4,1.3
53,6,3.4,4.5,1.6
54,6.3,3.3,4.7,1.6
55,5.5,2.5,4,1.3
56,4.8,3.4,1.6,0.2
57,6,3,4.8,1.8
58,6.7,3.3,5.7,2.5
59,7.9,3.8,6.4,2
60,5.2,4.1,1.5,0.1
61,4.8,3.4,1.9,0.2
62,5.6,2.9,3.6,1.3
63,6,2.7,5.1,1.6
64,6.7,3.1,4.7,1.5
65,6.1,2.6,5.6,1.4
66,5.2,3.5,1.5,0.2
67,5.1,3.5,1.4,0.3
68,5.8,2.7,4.1,1
69,6.2,2.9,4.3,1.3
70,4.8,3.1,1.6,0.2
71,7.6,3,6.6,2.1
72,5.7,2.6,3.5,1
73,5.4,3.9,1.7,0.4
74,7,3.2,4.7,1.4
75,6,2.9,4.5,1.5
76,4.9,3,1.4,0.2
77,6.4,2.7,5.3,1.9
78,6.2,3.4,5.4,2.3
79,5.7,2.5,5,2
80,6.1,3,4.6,1.4
81,7.2,3.6,6.1,2.5
82,5.1,3.7,1.5,0.4
83,7.1,3,5.9,2.1
84,6.3,2.9,5.6,1.8
85,6.3,2.8,5.1,1.5
86,5.9,3.2,4.8,1.8
87,5.8,2.7,5.1,1.9
88,6.5,3,5.5,1.8
89,6.7,3.1,5.6,2.4
90,6.9,3.2,5.7,2.3
91,6.5,3,5.8,2.2
92,5,2,3.5,1
93,5.5,2.4,3.8,1.1
94,5,2.3,3.3,1
95,4.5,2.3,1.3,0.3
96,5.4,3.9,1.3,0.4
97,5.5,2.4,3.7,1
98,5.4,3,4.5,1.5
99,4.9,3.6,1.4,0.1
100,5.7,3.8,1.7,0.3
101,5.1,2.5,3,1.1
102,6.4,2.8,5.6,2.2
103,6.9,3.1,5.4,2.1
104,5.7,4.4,1.5,0.4
105,5.4,3.4,1.7,0.2
106,5,3.4,1.6,0.4
107,5.1,3.8,1.5,0.3
108,6.4,3.1,5.5,1.8
109,6.6,3,4.4,1.4
110,7.4,2.8,6.1,1.9
111,4.9,2.4,3.3,1
112,5,3.4,1.5,0.2
113,6.4,2.8,5.6,2.1
114,5.1,3.8,1.9,0.4
115,6.9,3.1,5.1,2.3
116,5.8,2.7,5.1,1.9
117,5,3.6,1.4,0.2
118,7.2,3.2,6,1.8
119,6.5,3,5.2,2
120,6.3,2.5,5,1.9
121,7.7,2.8,6.7,2
122,6.3,3.4,5.6,2.4
123,6.3,2.3,4.4,1.3
124,6.1,2.9,4.7,1.4
125,5.2,3.4,1.4,0.2
126,6.3,3.3,6,2.5
127,5.9,3,4.2,1.5
128,6.7,3.1,4.4,1.4
129,5.7,2.8,4.1,1.3
130,4.7,3.2,1.6,0.2
131,7.7,3.8,6.7,2.2
132,4.3,3,1.1,0.1
133,4.4,2.9,1.4,0.2
134,5.1,3.4,1.5,0.2
135,4.6,3.4,1.4,0.3
136,4.6,3.6,1,0.2
137,5,3,1.6,0.2
138,5.7,2.9,4.2,1.3
139,4.7,3.2,1.3,0.2
140,5.6,2.8,4.9,2
141,5.2,2.7,3.9,1.4
142,5.8,2.8,5.1,2.4
143,5.7,3,4.2,1.2
144,7.7,2.6,6.9,2.3
145,6.4,3.2,4.5,1.5
146,5.1,3.3,1.7,0.5
147,4.8,3,1.4,0.1
148,6.8,3.2,5.9,2.3
149,5.4,3.4,1.5,0.4
150,6.5,2.8,4.6,1.5
1 Sepal.Length Sepal.Width Petal.Length Petal.Width
2 1 6.2 2.8 4.8 1.8
3 2 6.2 2.2 4.5 1.5
4 3 6.7 3.3 5.7 2.1
5 4 4.9 2.5 4.5 1.7
6 5 6.7 2.5 5.8 1.8
7 6 5.3 3.7 1.5 0.2
8 7 6.3 2.5 4.9 1.5
9 8 6.1 2.8 4.7 1.2
10 9 6 2.2 5 1.5
11 10 6.8 2.8 4.8 1.4
12 11 5.5 4.2 1.4 0.2
13 12 5 3.2 1.2 0.2
14 13 NA 2.7 4.2 1.3
15 14 6.8 3 5.5 2.1
16 15 4.6 3.2 1.4 0.2
17 16 6.1 3 4.9 1.8
18 17 5 3.5 1.6 0.6
19 18 6.9 3.1 4.9 1.5
20 19 7.2 3 5.8 1.6
21 20 4.8 3 1.4 0.3
22 21 6.4 3.2 5.3 2.3
23 22 5.6 3 4.1 1.3
24 23 4.9 3.1 1.5 0.1
25 24 4.4 3 1.3 0.2
26 25 5.4 3.7 1.5 0.2
27 26 4.9 3.1 1.5 0.2
28 27 6 NA 4 1
29 28 6.7 3 5 1.7
30 29 7.3 2.9 6.3 1.8
31 30 6.6 2.9 4.6 1.3
32 31 4.4 3.2 1.3 0.2
33 32 5.6 2.5 3.9 1.1
34 33 6.1 2.8 4 1.3
35 34 5.7 2.8 4.5 1.3
36 35 5.5 3.5 1.3 0.2
37 36 5.5 2.6 4.4 1.2
38 37 5 3.5 1.3 0.3
39 38 5.6 3 4.5 1.5
40 39 5.1 3.8 1.6 0.2
41 40 5.8 2.6 4 1.2
42 41 5.1 3.5 1.4 0.2
43 42 6.5 3.2 5.1 2
44 43 4.6 3.1 1.5 0.2
45 44 6.4 2.9 4.3 1.3
46 45 5 3.3 1.4 0.2
47 46 5.9 3 5.1 1.8
48 47 5.8 4 1.2 0.2
49 48 5.8 2.7 3.9 1.2
50 49 6.3 2.7 4.9 1.8
51 50 7.7 3 6.1 2.3
52 51 6.7 3 5.2 2.3
53 52 5.5 2.3 4 1.3
54 53 6 3.4 4.5 1.6
55 54 6.3 3.3 4.7 1.6
56 55 5.5 2.5 4 1.3
57 56 4.8 3.4 1.6 0.2
58 57 6 3 4.8 1.8
59 58 6.7 3.3 5.7 2.5
60 59 7.9 3.8 6.4 2
61 60 5.2 4.1 1.5 0.1
62 61 4.8 3.4 1.9 0.2
63 62 5.6 2.9 3.6 1.3
64 63 6 2.7 5.1 1.6
65 64 6.7 3.1 4.7 1.5
66 65 6.1 2.6 5.6 1.4
67 66 5.2 3.5 1.5 0.2
68 67 5.1 3.5 1.4 0.3
69 68 5.8 2.7 4.1 1
70 69 6.2 2.9 4.3 1.3
71 70 4.8 3.1 1.6 0.2
72 71 7.6 3 6.6 2.1
73 72 5.7 2.6 3.5 1
74 73 5.4 3.9 1.7 0.4
75 74 7 3.2 4.7 1.4
76 75 6 2.9 4.5 1.5
77 76 4.9 3 1.4 0.2
78 77 6.4 2.7 5.3 1.9
79 78 6.2 3.4 5.4 2.3
80 79 5.7 2.5 5 2
81 80 6.1 3 4.6 1.4
82 81 7.2 3.6 6.1 2.5
83 82 5.1 3.7 1.5 0.4
84 83 7.1 3 5.9 2.1
85 84 6.3 2.9 5.6 1.8
86 85 6.3 2.8 5.1 1.5
87 86 5.9 3.2 4.8 1.8
88 87 5.8 2.7 5.1 1.9
89 88 6.5 3 5.5 1.8
90 89 6.7 3.1 5.6 2.4
91 90 6.9 3.2 5.7 2.3
92 91 6.5 3 5.8 2.2
93 92 5 2 3.5 1
94 93 5.5 2.4 3.8 1.1
95 94 5 2.3 3.3 1
96 95 4.5 2.3 1.3 0.3
97 96 5.4 3.9 1.3 0.4
98 97 5.5 2.4 3.7 1
99 98 5.4 3 4.5 1.5
100 99 4.9 3.6 1.4 0.1
101 100 5.7 3.8 1.7 0.3
102 101 5.1 2.5 3 1.1
103 102 6.4 2.8 5.6 2.2
104 103 6.9 3.1 5.4 2.1
105 104 5.7 4.4 1.5 0.4
106 105 5.4 3.4 1.7 0.2
107 106 5 3.4 1.6 0.4
108 107 5.1 3.8 1.5 0.3
109 108 6.4 3.1 5.5 1.8
110 109 6.6 3 4.4 1.4
111 110 7.4 2.8 6.1 1.9
112 111 4.9 2.4 3.3 1
113 112 5 3.4 1.5 0.2
114 113 6.4 2.8 5.6 2.1
115 114 5.1 3.8 1.9 0.4
116 115 6.9 3.1 5.1 2.3
117 116 5.8 2.7 5.1 1.9
118 117 5 3.6 1.4 0.2
119 118 7.2 3.2 6 1.8
120 119 6.5 3 5.2 2
121 120 6.3 2.5 5 1.9
122 121 7.7 2.8 6.7 2
123 122 6.3 3.4 5.6 2.4
124 123 6.3 2.3 4.4 1.3
125 124 6.1 2.9 4.7 1.4
126 125 5.2 3.4 1.4 0.2
127 126 6.3 3.3 6 2.5
128 127 5.9 3 4.2 1.5
129 128 6.7 3.1 4.4 1.4
130 129 5.7 2.8 4.1 1.3
131 130 4.7 3.2 1.6 0.2
132 131 7.7 3.8 6.7 2.2
133 132 4.3 3 1.1 0.1
134 133 4.4 2.9 1.4 0.2
135 134 5.1 3.4 1.5 0.2
136 135 4.6 3.4 1.4 0.3
137 136 4.6 3.6 1 0.2
138 137 5 3 1.6 0.2
139 138 5.7 2.9 4.2 1.3
140 139 4.7 3.2 1.3 0.2
141 140 5.6 2.8 4.9 2
142 141 5.2 2.7 3.9 1.4
143 142 5.8 2.8 5.1 2.4
144 143 5.7 3 4.2 1.2
145 144 7.7 2.6 6.9 2.3
146 145 6.4 3.2 4.5 1.5
147 146 5.1 3.3 1.7 0.5
148 147 4.8 3 1.4 0.1
149 148 6.8 3.2 5.9 2.3
150 149 5.4 3.4 1.5 0.4
151 150 6.5 2.8 4.6 1.5

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P=matrix(c(_______),2,2) #输入如题目中所示矩阵 (3分)
P2=P_______P #在划线处填写合适的的运算符，求出两步状态转移概率矩阵 (2分)
P0=c(0.5,0.5) #初始概率向量
___________#预测2个周期后的概率向量 (3分)
cat("2个周期后，处于状态1的概率是：",_______) #根据题目运行结果填写，不要四舍五入 (2分)