Someone on Cross-validated was able to give me an answer, and it is
something I should have seen. classify uses a uniform prior, while
ClassificationDisciminant uses an empirical prior. Problem solved.
On Mon, Feb 18, 2013 at 3:31 PM, David Reed wrote:
> Ahh, I have used Gist, but am absent m
Ahh, I have used Gist, but am absent minded today it seems.
https://gist.github.com/dvreed77/4980426
On Mon, Feb 18, 2013 at 3:23 PM, Andreas Mueller
wrote:
> On 02/18/2013 09:07 PM, David Reed wrote:
> > So I came up with this small test script to show the difference
> > between Matlab's class
On 02/18/2013 09:07 PM, David Reed wrote:
> So I came up with this small test script to show the difference
> between Matlab's classify function and Matlab's
> ClassificationDiscriminant function. It appears that for balanced
> classes, they perform identically, but when you unbalance them you
So I came up with this small test script to show the difference between
Matlab's classify function and Matlab's ClassificationDiscriminant
function. It appears that for balanced classes, they perform identically,
but when you unbalance them you get radically different answers. This
problem become
Yes that is the method I was using, and its not giving the same results.
I'm going to keep working on getting some sim data.
On Fri, Feb 15, 2013 at 5:01 AM, Andreas Mueller
wrote:
> On 02/15/2013 02:10 AM, David Reed wrote:
>
> Could you link that?
>
>
> http://www.mathworks.de/products/stati
On 02/15/2013 02:10 AM, David Reed wrote:
Could you link that?
http://www.mathworks.de/products/statistics/examples.html?file=/products/demos/shipping/stats/classdemo.html#3
"The classify function can perform classification using different types
of discriminant analysis. First classify the da
Could you link that?
I found a function in Matlab, ClassificationDiscriminant, that performs
exactly the same as Python and R. So what is the real difference between
calling the classify algorithm in Matlab and this ClassificationDiscriminant
function?
On Thu, Feb 14, 2013 at 4:14 PM, wrote:
>
matlab doc online says linear classifier is lda by default.
Andrew Winterman schrieb:
>Logistic regression can be used as a linear classifier. Maybe that's
>matlab's linear classifier?
>
>On Thursday, February 14, 2013, David Reed wrote:
>
>> I was mistaken, R is providing the exact same resu
Logistic regression can be used as a linear classifier. Maybe that's
matlab's linear classifier?
On Thursday, February 14, 2013, David Reed wrote:
> I was mistaken, R is providing the exact same results as Python. Is
> there a difference between a linear classifer and LDA? Matlab never uses
>
I was mistaken, R is providing the exact same results as Python. Is there
a difference between a linear classifer and LDA? Matlab never uses the
words Linear Discriminant Analysis, its just says linear classifier, but is
giving different results than these other two software packages.
On Thu,
I don't think I can provide the data, but I'm trying to create some
simulated data that produces a similar difference.
I was just messing with R, and for LDA got a different result from the
other 2. I wonder if its just something I am doing wrong.
On Thu, Feb 14, 2013 at 10:07 AM, Andreas Muel
On 02/14/2013 04:04 PM, Andreas Mueller wrote:
> On 02/14/2013 03:59 PM, David Reed wrote:
>> I dont think this is the problem. My data is definetly oversampled, I
>> have 5000 samples for the 1 feature.
>>
>> I also should say that the problem that led be to LDA was seeing there
>> was a large bi
On 02/14/2013 03:59 PM, David Reed wrote:
> I dont think this is the problem. My data is definetly oversampled, I
> have 5000 samples for the 1 feature.
>
> I also should say that the problem that led be to LDA was seeing there
> was a large bias between SVM classification accuracy in sklearn an
I dont think this is the problem. My data is definetly oversampled, I have
5000 samples for the 1 feature.
I also should say that the problem that led be to LDA was seeing there was
a large bias between SVM classification accuracy in sklearn and matlab. I
am using the same parameters on both, an
Hi Dave.
It could be related to this bug:
https://github.com/scikit-learn/scikit-learn/issues/1649
But I'm just guessing.
If you could provide some toy data and the resulting models to
reproduce, we could try to hunt
down the problem.
Any help there would be much appreciated.
Cheers,
Andy
On
I was hoping I might be able to get some assistance here. I'm working on a
classification problem and have started to see some pretty
large discrepancies between results from Matlab and Sklearn.
The problem arises when doing univariate LDA. My set is fairly large with
an N of 5000, but he class
16 matches
Mail list logo
