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- NaN是什么 NaN == NaN 的结果是什么?为什么? - 知乎
NaN通常用于表示数学运算无法产生有意义的结果的情况，例如0除以0或对负数求平方根等。 NaN与任何其他值（包括NaN本身）进行比较的结果都是false，包括NaN == NaN。这是因为NaN被定义为不等于任何其他值，甚至不等于它自己。这是由于NaN的特殊性质导致的。
- What is the difference between NaN and NA? - Cross Validated
NA is for missing data NaN, as J M said is for arithmetic purpose NaN is usually the product of some arithmetic operation, such as 0 0 NA usually is declared in advance, or is a product of operation when you try to access something that is not there: > a <- c(1,2) > a[3] [1] NA
- 训练深度学习网络时候，出现Nan是什么原因，怎么才能避免？
训练深度学习网络时出现 NaN 的原因及避免方法 在训练深度学习网络时，NaN（Not a Number）是一个常见的问题。 它通常表示某些操作的结果无效或未定义，导致计算过程中的“数值错误”。
- r - Why do I get NAN for p-values while using statsmodels logit . . .
R GLM and statsmodels GLM have different ways of handling "perfect separation" (which is what is happening when fitted probabilities are 0 or 1) In Statsmodels, a fitted probability of 0 or 1 creates Inf values on the logit scale, which propagates through all the other calculations, generally giving NaN values for everything
- pytorch中第一轮训练loss就是nan是为什么啊？ - 知乎
全连接层只留下nn Linear(512,4096)，奇怪的事发生了，nan问题没有出现，第一次iteration后也没有出现nan，输出正常(但当然我的num_classes=10，这样肯定是不对的)，那试试nn Linear(512,10000)（全连接只有这一层，卷积层啥也没改），我去也没问题！
- NaN p-value when using Rs goodfit on binomial data
$\begingroup$ Hi Drew, sorry for my late answer Well, in case of zero frequencies, it is advised (at least I was taught so) to either merge categories, since Chi-square allows some 0 frequencies (less than 20% frequencies can be 0 when the factor has more than 2 levels), if that's reasonable, or to drop Chi-square and choose an alternative technique
- Why would R return NA as a lm () coefficient? - Cross Validated
I am fitting an lm() model to a data set that includes indicators for the financial quarter (Q1, Q2, Q3, making Q4 a default) Using lm(Y~ , data = data) I get a NA as the coefficient for Q3, and a
- How do I interpret NaN values in statsmodels. stats. anova_lm result
$\begingroup$ NaN is an absorbing operand for mathematical operations For example, a float plus a Nan is a Nan So first ensure that your original data is Nan-free The second issue that can come up which might produce a Nan is when an undefined operation, such as division by zero, is
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