我正在尝试对测试运行knn并训练数据。我的火车数据包含10000个观测值和33个变量，而测试数据包含1500个观测值和32个变量。我知道由于训练和测试中的变量数量不同而导致出现此错误，但是即使训练和测试中的变量数量不同，也有什么方法可以克服此错误并运行它吗？我已经尝试在测试数据集中添加另一列，并向其添加NA值，但这没有用。
这是我尝试运行的结果，它给了我我提到的错误。
library(class)
cl <- trainset$unique_id
knn.pred <- knn(trainset,testset,cl,k = 107)
我还尝试使用插入符包中的火车使用不同的代码来运行此代码，但是又出现了一个问题，即联系过多，因此我也不能这样做。
测试集
structure(list(unique_id = c(73928L, 3263L, 28243L, 21565L, 49267L,
21599L), metric1 = c(0L, 90L, 0L, 0L, 0L, 0L), metric2 = c(1L,
1L, 1L, 1L, 1L, 1L), metric6 = c(1L, 1L, 1L, 4L, 2L, 1L), metric3 = c(0,
0, 0, 326, 56, 0), metric4 = c(0, 6, 0, 978, 56, 0), metric5 = c(100,
0, 100, 0, 0, 100), binary_var1 = c(0L, 0L, 0L, 1L, 0L, 0L),
region = structure(c(215L, 170L, 199L, 59L, 63L, 170L), .Label = c("016ea69f855a716ec5e738506d1c6246",
"026d694c5c628393fe2d68b47cf1a808", "02d39f8c0bb8a6d74822c5b1325b6d52",
"04a5038c780ec3aa6a7124377d14577c", "05b6efe819965e5528b5de4f5a7a8d63",
"068a0b5b2858dc3f1ac7b47464bc4b0a", "06fa309b609b7c8f7c39a88abe2d507c",
"07fef9bb7fdb75c3be4801cc786d7aac", "08f461425ee5a5fb3197df665459ef97",
"090a4cbd8a5951a9b6312ec9491cfbd4", "097f0bcf6c5c038be7e1509b4737b423",
"0a394c8282da3440e523469562cfe696", "0b5853af814efb504db07f5bf0ed8d84",
"0bad206b82a2c718af4332280419b104", "0cee141d0d8d5eee1a2e57a1bac633c2",
"0daaf4a9abe3920c453a7f1f82a9bb19", "0eb635a109be482d973ed1c4a5fbb77a",
"0ef8f876d62a45352e28410454e3634b", "0f2a4050992e98c99c88f1b8ea533439",
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"11ea71f253acf02a2d126a0901e765a7", "130c7ca8daccb66ef614ec3331a0f665",
"146159057df3f8947f820d9fc184c6cd", "15e49475e42539feed93fc5cce25d3cb",
"1743af44b85a13e7050174fbd749250e", "185a5eb309e9ba14f65e6486f08b3032",
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"2078da3d3b101e997d874cc9f5686f00", "213fe69502445ed67ae8b99d22838802",
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), class = "factor"), dayHourMinute = c(2.01711e+11, 2.01711e+11,
2.01711e+11, 2.01711e+11, 2.01711e+11, 2.01711e+11), binary_var2 = c(0L,
1L, 0L, 0L, 0L, 0L), page1_top = c(0, 0, 0, 0, 0, 0), page1_exits = c(0,
0, 0, 0, 0, 0), visited_page1 = c(0L, 0L, 0L, 0L, 0L, 0L),
page2_top = c(0, 0, 0, 0, 0, 0), page2_exits = c(0, 0, 0,
0, 0, 0), visited_page2 = c(0L, 0L, 0L, 0L, 0L, 0L), page3_top = c(0,
0, 0, 0, 0, 0), page3_exits = c(0, 0, 0, 0, 0, 0), visited_page3 = c(0L,
0L, 0L, 0L, 0L, 0L), page4_top = c(0, 0, 0, 0, 0, 0), page4_exits = c(0,
0, 0, 0, 0, 0), visited_page4 = c(0L, 0L, 0L, 0L, 0L, 0L),
page5_top = c(0, 0, 0, 0, 0, 0), page5_exits = c(0, 0, 0,
0, 0, 0), visited_page5 = c(0L, 0L, 0L, 0L, 0L, 0L), page6_top = c(0,
0, 0, 0, 0, 0), page6_exits = c(0, 0, 0, 0, 1, 1), visited_page6 = c(0L,
0L, 0L, 0L, 1L, 1L)), row.names = c(73928L, 3263L, 28243L,
21565L, 49267L, 21599L), class = "data.frame")
这应该适用于火车
答案 0 :(得分：1)
据我了解，某些功能仅在String age = "My name is John and I am 18 years old";
Matcher matcher = Pattern.compile("My name is John and I am ([\\w]*) years old").matcher(age);
if (matcher.matches()) {
System.out.println(Integer.parseInt(matcher.group(1)));
}
中可用。在这种情况下，只需从trainset中删除多余的列，因为它仍然无济于事。这是因为trainset没有进行任何实际的培训；看看我的other answer。
简而言之：knn在R 33 中具有矢量，而trainset在R 32 中具有矢量。然后，testset几乎唯一要做的就是计算这些向量之间的距离。由于knn没有其中一项功能，因此我们手动执行的操作只是删除testset向量的一个坐标，以将其缩小为32维，然后计算距离。但这与简单地运行
trainset如果说第13列是多余的列。