我有以下数据框:关于数据和框架的历史很少。这是第二版本初始数据帧具有基于列标题表示的实际相似度值。基于实际的相似度值,每个都已经通过它们所属的bin来识别,并且我认为bin是实际得分。
cosinFcolor cosinEdge cosinTexture histoFcolor histoEdge histoTexture jaccard
1 3 0 0 1 1 0 0
2 0 0 5 0 2 2 0
3 1 0 2 0 0 1 0
4 0 0 3 0 1 1 0
5 1 3 1 0 4 0 0
6 0 0 1 0 0 0 0
我想要做的是将每个行值相加并将其保存在jaccard列旁边的一列中,但在求和期间我想检查jaccard的值,这里是我想要做的sudo代码jaccard值:
这是SUDO CODE:
If jaccard.value of that row == 5
(cosinFcolor + cosinEdge + cosinTexture + histoFcolor + histoEdge + histoTexture) += (jaccard.value of the row * .5)
If jaccard.value of that row == 4
(cosinFcolor + cosinEdge + cosinTexture + histoFcolor + histoEdge + histoTexture) += (jaccard.value of the row * .4)
If jaccard.value of that row == 3
(cosinFcolor + cosinEdge + cosinTexture + histoFcolor + histoEdge + histoTexture)+= (jaccard.value of the row * .3)
If jaccard.value of that row == 2
(cosinFcolor + cosinEdge + cosinTexture + histoFcolor + histoEdge + histoTexture) += (jaccard.value of the row * .2)
If jaccard.value of that row == 1
(cosinFcolor + cosinEdge + cosinTexture + histoFcolor + histoEdge + histoTexture) += (jaccard.value of the row * .1)
else if jaccard.value of that row == 0
value in the new column is = -1
完成此操作后,我希望得到如下所示的最终数据框:
cosinFcolor cosinEdge cosinTexture histoFcolor histoEdge histoTexture jaccard weightedScore
1 3 0 0 1 1 0 0 -1
2 0 0 5 0 2 2 0 -1
3 1 0 2 0 0 1 0 -1
4 0 0 3 0 1 1 0 -1
5 1 3 1 0 4 0 0 -1
6 0 0 1 0 0 0 0 -1
7 0 0 1 0 0 0 1 1.1
我的初始(第一个数据框架,我已经放置)是通过使用帮助StackOverflow用户跟随R代码生成的:
这是R代码:
single_img_sim_no_title <- single_img_similarity
single_img_sim_no_title$title <- NULL
head(single_img_sim_no_title)
#converting it to bins
sing_img_bins <- apply(single_img_sim_no_title, 2, cut, c(-Inf, seq(0.5, 1, 0.1), Inf), labels=0:6)
sing_img_bins[sing_img_bins=="6"] <- "0"
sing_img_bins <- as.data.frame(sing_img_bins)