Displaying 5 results from an estimated 5 matches for "mvida".
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vida
2005 Feb 25
4
Temporal Analysis of variable x; How to select the outlier threshold in R?
For a financial data set with large variance, I'm trying to find the
outlier threshold of one variable "x" over a two year period. I
qqplot(x2001, x2002) and found a normal distribution. The latter part of
the normal distribution did not look linear though. Is there a suitable
method in R to find the outlier threshold of this variable from 2001 and
2002 in R?
2005 Feb 20
2
matrix operations
In R, I'm imported a data frame of 2,321,123 by 4 called "dataF".
I converted the data frame "dataF" to a matrix
dataM <- as.matrix(dataF)
Does R have an efficient routine to treat the special elements that
contain "inf" in them. For example, can you separate the rows that have
"inf" elements from the matrix into a separate matrix without
2005 Feb 25
2
outlier threshold
For the analysis of financial data wih a large variance, what is the best way to select an outlier threshold?
Listed below, is there a best method to select an outlier threshold and how does R calculate it?
In R, how do you find the outlier threshold through an interquartile range?
In R, how do you find the outlier threshold using the hist command?
In R, how do you find the outlier threshold
2005 Mar 23
1
Gini's Importance Value Variable = Inf
Hi All,
In the script below, the importance measure for column 4 (ie
MeanDecreaseGini) indicated "Inf" for V7.
Running the getTree command showed that "V7" had been selected at least
twice in one of the trees for Random Forest. So the "Inf" command was
not generated as a result of dividing the sum of the decreases by 0.
Any suggestions on what may be causing the
2005 Mar 22
2
Error: Can not handle categorical predictors with more than 32 categories.
Hi All,
My question is in regards to an error generated when using randomForest
in R. Is there a special way to format the data in order to avoid this
error, or am I completely confused on what the error implies?
"Error in randomForest.default(m, y, ...) :
Can not handle categorical predictors with more than 32 categories."
This is generated from the command line:
>