plotDominationGraph(TunePareto)
plotDominationGraph()所属R语言包：TunePareto
Visualize the Pareto fronts of parameter configuration scores
可视化的帕累托方面的参数配置分数
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Draws the Pareto fronts and domination relations of tested parameter configurations in a graph. Here, the leftmost column of nodes represents the non-dominated configurations (i.e. the first Pareto front). The second column contains the second Pareto front, i.e. the configurations that are only dominated by the first Pareto front, and so on. An edge between two configurations indicate that the first configuration is dominated by the second.
绘制的帕累托方面和统治关系图中的测试参数配置。在这里，最左边的列的节点表示的非支配配置（即第一帕累托前面）。第二列包含第二Pareto前沿，即只由第一Pareto前沿为主的配置，等等。的边缘之间的两种配置表明，在第一结构主要是由所述第二。
用法----------Usage----------
plotDominationGraph(tuneParetoResult,
transitiveReduction = TRUE,
drawDominatedObjectives = TRUE,
drawLabels = TRUE,
drawLegend = TRUE,
x.legend = "topleft",
cex.legend = 0.7,
col.indicator,
pch.indicator = 15,
cex.indicator = 0.8,
...)
参数----------Arguments----------
参数：tuneParetoResult
An object of class TuneParetoResult as returned by tunePareto.
类的一个对象TuneParetoResult返回的tunePareto。
参数：transitiveReduction
If this is true, transitive edges in the graph are removed to enhance readability. That is, if configuration c1 dominates configuration c2 and c2 dominates c3, no edge from c3 to c1 is drawn.
如果这是真的，可传递图中的边删除，以提高可读性。也就是说，如果配置c1占主导地位的配置c2和c2占主导地位c3，没有边缘c3到c1绘制。
参数：drawDominatedObjectives
If set to true, color indicators are drawn next to the nodes. Here, each color corresponds to one objective. The color is drawn next to a node if this node has the best score in this objectives among all solutions of the same Pareto front (i.e., column of the graph).
如果设置为true，颜色指示灯旁边绘制的节点。在这里，每种颜色对应一个目标。颜色画下一个节点，如果该节点在这个目标的最好成绩相同的帕累托前（即，列在图表）所有的解决方案中。
参数：drawLabels
Specifies whether the parameter configurations should be printed next to the corresponding edges.
指定是否应印下的对应边的参数配置。
参数：drawLegend
If drawDominatedObjectives=TRUE, this specifies whether a legend with the objective colors should be drawn.
如果drawDominatedObjectives=TRUE，指定是否应当制定一个传奇的目标颜色。
参数：x.legend
The position of the legend. For details, refer to the x parameter of legend.
位置的传说。有关详细信息，请参阅x参数legend。
参数：cex.legend
Specifies the size of the text in the legend if drawLegend is true.
指定如果drawLegend是真正的传说中的文本大小。
参数：col.indicator
Specifies an optional list of colors, one for each objective function. These colors will be used for the indicators if drawDominatedObjectives is true. By default, a predefined set of colors is used.
指定一个可选的颜色列表，每个目标的功能之一。将使用这些颜色，如果drawDominatedObjectives是真正的指标。默认情况下，使用一组预定义的颜色。
参数：pch.indicator
Specifies a single plotting character or a list of plotting characters for the objective functions in the indicators which is used for the indicators if drawDominatedObjectives is true.
指定一个单一的绘图如果drawDominatedObjectives是真正的指标的指标，用于不同的目标函数在绘制字符的字符或列表。
参数：cex.indicator
Specifies the size of the symbols in the indicators which is be used for the indicators if drawDominatedObjectives is true. This can also be a vector of sizes for the symbols of the objectives.
指定的大小的指标中的符号被用于如果drawDominatedObjectives是真实的指标。这也可以是一个向量的符号的目标的尺寸。
参数：...
Further graphical parameters for plot.igraph.
进一步的图形参数为plot.igraph。
值----------Value----------
Invisibly returns the igraph object representing the graph.
无形返回igraph对象的图形。
参见----------See Also----------
tunePareto
tunePareto
实例----------Examples----------
# call tunePareto using a k-NN classifier [呼叫tunePareto使用K-NN分类]
# with different 'k' and 'l' on the 'iris' data set[与不同的k和L上的IRIS数据集]
x <- tunePareto(data = iris[, -ncol(iris)],
labels = iris[, ncol(iris)],
classifier = tunePareto.knn(),
k = c(5,7,9),
l = c(1,2,3),
objectiveFunctions=list(cvError(10, 10),
cvSpecificity(10, 10, caseClass="setosa")))
# plot the graph [绘制图形]
plotDominationGraph(x)
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注：
注1：为了方便大家学习，本文档为生物统计家园网机器人LoveR翻译而成，仅供个人R语言学习参考使用，生物统计家园保留版权。
注2：由于是机器人自动翻译，难免有不准确之处，使用时仔细对照中、英文内容进行反复理解，可以帮助R语言的学习。
注3：如遇到不准确之处，请在本贴的后面进行回帖，我们会逐渐进行修订。
|
发表于 2012-10-1 12:58:31
