Hello everyone,
I use ' IsolationForest' to pick up the outlier data today and I notice
there is a ' contamination ' parameter in IsolationForest function, and its
default value is 0.1 = 10%
So is there a way to pick the outlier without assigning the proportion of
outliers in the da
On 24/11/16 09:00, Jaidev Deshpande wrote:
>
> well, `param_grid` in GridSearchCV can also be a list of dictionaries,
> so you could directly specify the cases you are interested in (instead
> of the full grid - exceptions), which might be simpler?
>
>
> Actually now that I think of
> many of them need number of outlier and distance as input parameter in
> advance, is there algorithm more intelligently ?
With ‘intelligently’ you mean ‘more automatic’ (fewer hyperparameters to define
manually)? In my opinion, “outlier” is a highly context-specific definition,
thus, it’s rea
Hi,
I am facing some problem with the "BayesianGaussianMixture" function, but I
do not know if it is because of my poor knowledge on this type of
statistics or if it is something related to the algorithm. I have set of
data of around 1000 to 4000 observation (every feature is a spectrum of
around
Typically this means that the model is so confident in its predictions it
does not believe it possible for the sample to come from the other
component. Do you get the same results with a regular GaussianMixture?
On Fri, Nov 25, 2016 at 11:34 AM, Tommaso Costanzo <
[email protected]> wro
On Fri, 25 Nov 2016 at 20:24 Roman Yurchak wrote:
> On 24/11/16 09:00, Jaidev Deshpande wrote:
> >
> > well, `param_grid` in GridSearchCV can also be a list of
> dictionaries,
> > so you could directly specify the cases you are interested in
> (instead
> > of the full grid - exception
