Contribute at least one answer each month for 12 consecutive months
2017年7月20日授予汤姆·莱恩
回答3个超过30天的未得到答复的问题
2017年7月20日授予汤姆·莱恩
100of your answers have been accepted
2017年7月20日授予汤姆·莱恩
Provide your first answer ever to someone else's question
2017年7月20日授予汤姆·莱恩
Solve a problem for the first time
2012年4月23日授予汤姆·莱恩
内容提要
回答
警告：最大似然估计没有收敛。功能评估限制超出了。
Since the random numbers vary, it makes sense that the number of iterations will also vary so the number of warnings may change....
警告：最大似然估计没有收敛。功能评估限制超出了。
Since the random numbers vary, it makes sense that the number of iterations will also vary so the number of warnings may change....
2years ago | 1
|accepted
回答
非线性拟合到具有共享参数的多个数据集
My posted answer from 11-Dec-2012 shows how to deal with multiple datasets following roughly the same functional form with param...
非线性拟合到具有共享参数的多个数据集
My posted answer from 11-Dec-2012 shows how to deal with multiple datasets following roughly the same functional form with param...
2years ago | 0
回答
非线性拟合到具有共享参数的多个数据集
My posted answer from 11-Dec-2012 shows how to deal with multiple datasets that are roughly similar. That isn't necessary, thoug...
非线性拟合到具有共享参数的多个数据集
My posted answer from 11-Dec-2012 shows how to deal with multiple datasets that are roughly similar. That isn't necessary, thoug...
2years ago | 0
回答
Curve fitting: seversl curves to one
如果您要nhh = a *（n1^b） *（n2^c） *（n3^d）考虑获取日志log（nhh）= log（a） + b * log（n1） + c * log（n2）+ D ...
Curve fitting: seversl curves to one
如果您要nhh = a *（n1^b） *（n2^c） *（n3^d）考虑获取日志log（nhh）= log（a） + b * log（n1） + c * log（n2）+ D ...
2years ago | 0
回答
我是否从MATLAB许可证中分别购买统计和机器学习工具箱？
There may be other options. If the GUI author can work with you, you may be able to replace use of tdfread by a newer core MATLA...
我是否从MATLAB许可证中分别购买统计和机器学习工具箱？
There may be other options. If the GUI author can work with you, you may be able to replace use of tdfread by a newer core MATLA...
3年前|0
回答
核密度估计具有选择的带宽，然后将密度函数（CDF）归一化，从而使CDF的积分从min到最大等于1；然后采用CDF的第一个和第二个衍生物
You seem to want to do a number of things including integrating and specifying a bandwidth. Maybe this will get you started. ...
核密度估计具有选择的带宽，然后将密度函数（CDF）归一化，从而使CDF的积分从min到最大等于1；然后采用CDF的第一个和第二个衍生物
You seem to want to do a number of things including integrating and specifying a bandwidth. Maybe this will get you started. ...
4年前|0
回答
How to perform stratified 10 fold cross validation for classification in MATLAB?
如果您有统计信息和机器学习工具箱，请考虑| cvpartition |功能。它可以定义分层样品。
How to perform stratified 10 fold cross validation for classification in MATLAB?
如果您有统计信息和机器学习工具箱，请考虑| cvpartition |功能。它可以定义分层样品。
5 years ago | 1
|accepted
回答
Conflicting results with multcompare when using the Kruskal-Wallis test on multiple groups
It's sad but true that there can be an overall difference according to one test, another test might not declare specific differe...
Conflicting results with multcompare when using the Kruskal-Wallis test on multiple groups
It's sad but true that there can be an overall difference according to one test, another test might not declare specific differe...
5 years ago | 0
回答
每个分布的日志可能性。
It's not clear to me what fails to match with what. These match: >> x = -5*log(rand(100,1)); >> pd = fitdist(x,'weibull'...
每个分布的日志可能性。
It's not clear to me what fails to match with what. These match: >> x = -5*log(rand(100,1)); >> pd = fitdist(x,'weibull'...
5 years ago | 1
|accepted
回答
贝叶斯逻辑回归 - 切片样本 - 查找机器学习参数
It looks like you have the right idea. But I suspect the calculations are underflowing. You're multiplying thousands of probabil...
贝叶斯逻辑回归 - 切片样本 - 查找机器学习参数
It looks like you have the right idea. But I suspect the calculations are underflowing. You're multiplying thousands of probabil...
6 years ago | 1
回答
how to identify a fitglm output as being rank deficient from the resulting object
If your model is f, you could see if f.NumCoefficients > f.NumEstimatedCoefficients
how to identify a fitglm output as being rank deficient from the resulting object
If your model is f, you could see if f.NumCoefficients > f.NumEstimatedCoefficients
6 years ago | 0
回答
如何计算阵列和矩阵之间的相关系数？
If you have the Statistics and Machine Learning Toolbox, it sounds like you want this: >> x = randn(20,3); >> y = x*[1 0...
如何计算阵列和矩阵之间的相关系数？
If you have the Statistics and Machine Learning Toolbox, it sounds like you want this: >> x = randn(20,3); >> y = x*[1 0...
6 years ago | 0
|accepted
回答
Unable to access Stats toolbox functions
工具箱函数anova1, anova2 anovan,and rmanova among others. It does not have functions anova or ranova. Howev...
Unable to access Stats toolbox functions
工具箱函数anova1, anova2 anovan,and rmanova among others. It does not have functions anova or ranova. Howev...
6 years ago | 1
回答
Plotslice-图下方的数字是多少？
The prediction shown at the left of the plot is the value given by the model when the predictors are set to the numbers shown be...
Plotslice-图下方的数字是多少？
The prediction shown at the left of the plot is the value given by the model when the predictors are set to the numbers shown be...
6 years ago | 3
|accepted
回答
渐进式函数是否能够使用调整后的R平方而代替p值评估？
有一个较新的功能可以做到这一点：负载hald stepwiselm（成分，热，“标准”，“ jubsrsquared'）
渐进式函数是否能够使用调整后的R平方而代替p值评估？
有一个较新的功能可以做到这一点：负载hald stepwiselm（成分，热，“标准”，“ jubsrsquared'）
6 years ago | 1
|accepted
回答
回归函数和FITLM函数有什么区别
Take a look at the 12th and 13th columns of X. It looks to me like the 12th may be constant or may differ by a constant from the...
回归函数和FITLM函数有什么区别
Take a look at the 12th and 13th columns of X. It looks to me like the 12th may be constant or may differ by a constant from the...
6 years ago | 0
回答
决策树，只有二进制分支？
如果您将分类树适合到著名的Fisher Iris数据，则可以得到：>>加载Fisheriris >> F = Fitctree（MES，S ... ...
决策树，只有二进制分支？
如果您将分类树适合到著名的Fisher Iris数据，则可以得到：>>加载Fisheriris >> F = Fitctree（MES，S ... ...
6 years ago | 0
|accepted
回答
Separate Drawing of Gaussian Mixture Model
You did something like this: x = [randn(4000,1)/2; 5+2*randn(6000,1)]; f = fitgmdist(x,2); histogram(x,'Normalization...
Separate Drawing of Gaussian Mixture Model
You did something like this: x = [randn(4000,1)/2; 5+2*randn(6000,1)]; f = fitgmdist(x,2); histogram(x,'Normalization...
6 years ago | 2
|accepted
回答
为什么置信区间分布与分布重叠？
A couple of things. First, take out your truncate statements and run the code. You'll see that the "LB" cdf is substantially bel...
为什么置信区间分布与分布重叠？
A couple of things. First, take out your truncate statements and run the code. You'll see that the "LB" cdf is substantially bel...
6 years ago | 0
回答
fitnlm w/ w/ table使用并非所有变量
You can specify modelfun using variable names: load carsmall t = table(MPG,Weight,Origin) nlm = fitnlm(t,'MPG~b1+b2*W...
fitnlm w/ w/ table使用并非所有变量
You can specify modelfun using variable names: load carsmall t = table(MPG,Weight,Origin) nlm = fitnlm(t,'MPG~b1+b2*W...
6 years ago | 0
|accepted
回答
使用PCA减少MATLAB的尺寸
The first component explains most of the variation in the columns of DATA, but Y is not involved in that. Of course I don't unde...
使用PCA减少MATLAB的尺寸
The first component explains most of the variation in the columns of DATA, but Y is not involved in that. Of course I don't unde...
6 years ago | 1
|accepted
