刚刚在R中发现了Lime包,并仍在尝试完全理解该包。我被'plot_features‘的可视化给难住了
请原谅我的天真。
我的问题是,每一行的案例编号是连续的吗?换句话说,案例416是否等同于数据中的第416行?如果不是,我如何知道每个案例编号所引用的行?

重现上图的示例代码:
library(MASS)
library(lime)
data(biopsy)
biopsy$ID <- NULL
biopsy <- na.omit(biopsy)
biopsy2 = data.frame(ID = 1:nrow(biopsy), biopsy)
names(biopsy2) <- c('ID','clump thickness', 'uniformity of cell size',
'uniformity of cell shape', 'marginal adhesion',
'single epithelial cell size', 'bare nuclei',
'bland chromatin', 'normal nucleoli', 'mitoses',
'class')
# Now we'll fit a linear discriminant model on all but 4 cases
set.seed(4)
test_set <- sample(seq_len(nrow(biopsy2)), 4)
prediction <- biopsy2$class
biopsy2$class <- NULL
model <- lda(biopsy2[-test_set, ], prediction[-test_set])
predict(model, biopsy2[test_set, ])
explainer <- lime(biopsy2[-test_set,], model, bin_continuous = TRUE, quantile_bins = FALSE)
explanation <- explain(biopsy2[test_set, ], explainer, n_labels = 1, n_features = 4)
plot_features(explanation, ncol = 1)编辑:向活检表中添加了一个名为ID的额外列
发布于 2019-01-30 19:23:46
正如您在explanation中看到的,在该图中,我们从头开始逐个进行:
head(explanation[, 1:5])
model_type case label label_prob model_r2
1 classification 416 benign 0.9943635 0.5432439
2 classification 416 benign 0.9943635 0.5432439
3 classification 416 benign 0.9943635 0.5432439
4 classification 416 benign 0.9943635 0.5432439
5 classification 7 benign 0.9527375 0.6586789
6 classification 7 benign 0.9527375 0.6586789但是,由于每种情况都有多行,因此知道哪些行对应于它们可能不是一个坏主意。为此,您可以使用
which(416 == explanation$case)
# [1] 1 2 3 4所以
explanation[which(416 == explanation$case), 1:5]
# model_type case label label_prob model_r2
# 1 classification 416 benign 0.9949716 0.551287
# 2 classification 416 benign 0.9949716 0.551287
# 3 classification 416 benign 0.9949716 0.551287
# 4 classification 416 benign 0.9949716 0.551287https://stackoverflow.com/questions/54437172
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