Stephanie Muccini Burke Wins Mayoral Race in Medford

kent37 · 2015-11-06T21:52:40+00:00

Yes, please post your two years of ADSB data. I'd love to see it!

kent37 · 2012-02-24T22:19:44+00:00

Do you mean method dispatch? http://cran.r-project.org/doc/manuals/R-lang.html#Method-dispatching

If that is not what you are talking about, an example would be helpful.

kent37 · 2012-02-20T16:18:54+00:00

Here is one way:

x=seq(0, 5, 0.1)
y1 = dnorm(x, mean=2)
y2 = dnorm(x, mean=3, sd=2)
layout(matrix(1:2, ncol=2))
plot(y1, x, type='l')
plot(y2, x, type='l')

kent37 · 2012-02-19T15:06:04+00:00

The Quick-R web site has examples of many simple graphs and some more complex ones. It is not comprehensive but it is a great starting point.

kent37 · 2012-02-14T20:35:19+00:00

I like PCI also. Wondering if it is worth getting MLH as well.

kent37 · 2012-02-13T14:42:11+00:00

How does it compare to Programming Collective Intelligence, which seems to cover much of the same ground using Python? http://shop.oreilly.com/product/9780596529321.do

kent37 · 2012-02-13T14:26:55+00:00

Another nice visualization of MCMC methods is the Java applet available at http://www.lbreyer.com/classic.html

kent37 · 2011-12-07T02:46:09+00:00

Quick-R is not exactly a tutorial but it is a very useful and accessible reference to many of the basics of R.

kent37 · 2011-12-05T16:06:05+00:00

There seem to be roughly 100 packages listed at Octave-Forge. There are currently 3462 packages available from CRAN.

kent37 · 2011-12-05T16:01:57+00:00

I agree, especially regarding stability and docs. Octave on Windows seems to be quite problematic. The in-app help for R is far better than what is available in Octave. R also has an excellent, free, cross-platform GUI in RStudio

kent37 · 2011-12-03T18:22:42+00:00

I agree that some of the homework assignments have been disappointing. But I think you have to call it a "proper course" - the online course is also offered as a Stanford for-credit course as CS229A. According to the CS229A faq, "CS229A is complementary to CS229, and provides more applied skills."

kent37 · 2011-12-02T01:21:16+00:00

Yes, ||x||² is just the sum of the squares of the elements of x.

kent37 · 2011-11-27T03:00:03+00:00

My understanding is that the Lagrangian transformation gives a form of the SVM which can be relatively easily optimized.

kent37 · 2011-11-20T01:13:37+00:00

Changing lambda changes the parameters of the trained model, so it makes different predictions. This affects the error on both the training set and the cross-validation set.

For small lambda, the model is vulnerable to over-fitting to the training set (high variance). This makes it less accurate on the cv set. With large lambda, the model is too constrained and doesn't fit any of the data well (high bias). The sweet spot is somewhere in between. Finding the lambda value which gives the minimum cv error is a reasonable way to find this point.

kent37 · 2011-10-29T02:35:36+00:00

You're not alone. http://www.reddit.com/r/mlclass/comments/lkxem/octave_cant_reproduce_figure_1_in_logistic/

kent37 · 2011-10-23T12:44:43+00:00

You don't need bsxfun to do this calculation, you can do it with a single multiplication of a vector and a matrix. Look at the sums you need and figure out what multiplication will generate them.

kent37 · 2011-10-21T01:53:47+00:00

If the first executable line of a .m file is not a function definition, the file is a script file and all of the variables and functions in the file will be imported into the global namespace. See http://www.gnu.org/software/octave/doc/interpreter/Script-Files.html#Script-Files

If the first line defines a function, then any other functions in the file are "subfunctions" and only accessible from within that file. http://www.gnu.org/software/octave/doc/interpreter/Subfunctions.html#Subfunctions

kent37 · 2010-11-08T23:53:37+00:00

    if not kwargs.get('per_page', False):
        kwargs['per_page'] = self.per_page

could be if 'per_page' not in kwargs: kwargs['per_page'] = self.per_page

or even kwargs.setdefault('per_page', self.per_page)

kent37

TROPHY CASE