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-Original Message-
From: peter dalgaard [mailto:pda...@gmail.com]
Sent: Thursday, 10 July 2014 10:08 AM
To: Jeff Newmiller
Cc: Bert Gunter; Phan, Truong Q; r-help@r-project.org
Subject: Re: [R] R Studio v3.0.3 for Windows 32bits is too slow
Grumpy today, Jeff?
For the conc
Grumpy today, Jeff?
For the concrete issue, I'd conjecture that the base problem is that there are
way too many columns in the data and that the nature of the method is not
properly understood. It is not obvious that k-means clustering based on
Euclidean distance makes sense in 1426-dimensional
On 10/07/14 04:24, Jeff Newmiller wrote:
Grumpy today, Bert?
Bert is ***always*** grumpy! :-) If he weren't, I'd get worried.
But then someone else, not more than a million miles from this email,
has a strong tendency to be grumpy (acerbic?) as well.
Of course ***I*** am ***never*** gr
Grumpy today, Bert?
While it is a fact that RStudio is a separate tool from R, it is clear from the
question that the OP is interested in capabilities that R is providing and he
simply cannot tell the difference.
OP:
1) "Better" is a word that leads to pointless arguments. You will have to be
RStudio is a separate product with its own support. Post there, not here.
-- Bert
Bert Gunter
Genentech Nonclinical Biostatistics
(650) 467-7374
"Data is not information. Information is not knowledge. And knowledge
is certainly not wisdom."
Clifford Stoll
On Tue, Jul 8, 2014 at 7:34 PM, Phan
Hi R'er,
I have a dataset which has a matrix of 7502 x 1426 (rows x columns).
The data is in a CSV format which has a size around 68Mb. This dataset is less
than 10% of our dataset.
I have been adopting the Anomaly detection method as described by
http://www.mattpeeples.net/kmeans.html .
It has
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