accuracy(SDMTools)
accuracy()所属R语言包:SDMTools
Measures of Model Accuracy
模型精度的措施
译者:生物统计家园网 机器人LoveR
描述----------Description----------
accuracy estimates six measures of accuracy for presence-absence or presence-psuedoabsence data. These include AUC, ommission rates, sensitivity, specificity, proportion correctly identified and Kappa. <br> <br> Note: this method will exclude any missing data.
accuracy估计的准确度存在不存在或存在psuedoabsence数据的六项措施。这些措施包括AUC,OMMISSION率,灵敏度,特异性,比例正确识别和Kappa。 <br> <br>请注意:此方法将排除任何丢失的数据。
用法----------Usage----------
accuracy(obs,pred,threshold=0.5)
参数----------Arguments----------
参数:obs
a vector of observed values which must be 0 for absences and 1 for occurrences
必须为0缺勤和1出现的观测值的向量
参数:pred
a vector of the same length as obs representing the predicted values. Values must be between 0 & 1 prepresenting a likelihood.
obs表示的预测值相同的长度的矢量。值必须介于0和1之间的的可能性prepresenting。
参数:threshold
this can be: <br> a) a single value representing a single threshold between 0 & 1; <br> b) a vector of threshold values between 0 & 1; OR <br> c) an integer value representing the number of equal interval threshold values between 0 & 1
这可以是:<BR>一)单值介于0和1之间的一个阈值;参考阈值在0和1之间,或参考C)b)一个向量数的整数值,表示相等的间隔阈值的值在0和1之间的
值----------Value----------
a data.frame with seven columns:
七列数据框:
参数:threshold
the threshold values representing each row of data
代表每一行的数据的阈值
参数:AUC
the AUC given the defined threshold value
AUC定义的阈值
参数:ommission.rate
the ommission rate as a proportion of true occurrences misidentified given the defined threshold value
OMMISSION的真实发生率的比例误认为定义的阈值
参数:sensitivity
the sensitivity given the defined threshold value
灵敏度定义的阈值
参数:specificity
the specificity given the defined threshold value
具体定义的阈值
参数:prop.correct
the proportion of the presence and absence records correctly identified given the defined threshold value
正确确定之给定的比例存在和不存在记录所定义的阈值
参数:Kappa
the Kappa statistic of the model given the defined threshold value
Kappa统计的模型定义的阈值
(作者)----------Author(s)----------
Jeremy VanDerWal <a href="mailto:jjvanderwal@gmail.com">jjvanderwal@gmail.com</a>
参见----------See Also----------
auc, Kappa, omission, sensitivity, specificity, prop.correct, confusion.matrix
auc,Kappa,omission,sensitivity,specificity,prop.correct,confusion.matrix
实例----------Examples----------
#create some data[创建一些数据]
obs = c(sample(c(0,1),20,replace=TRUE),NA); obs = obs[order(obs)]
pred = runif(length(obs),0,1); pred = pred[order(pred)]
#calculate accuracy of the model with a single threshold value[用一个阈值计算模型的准确性]
accuracy(obs,pred,threshold=0.5)
#calculate accuracy given several defined thresholds[计算给出了几个定义的阈值精度]
accuracy(obs,pred,threshold=c(0.33,0.5,0.66))
#calculate accuracy given a number of equal interval thresholds[给定一个数相等的时间间隔阈值的计算精确度]
accuracy(obs,pred,threshold=20)
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。
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