Hi Darshan,
What i understand from your problem is that:
- You have clustered few documents
- You want to verify the accuracy of ur clustering , and you want to use
entropy for that
- You are not sure what should be the input for entropy calculation.
Possible solution:
The entropy would expect a S
to understand. Computing mutual
> information (not entropy) on the confusion matrix between two clusterings
> can also be done, but that also seems beyond the original question.
>
> As such, I think that the burden is on the original questioner to describe
> the problem more accurate
Hi, The donut.csv file you are looking for is present at -
./examples/src/main/resources/donut.csv
Peace,
Yash
On Fri, Jun 13, 2014 at 3:15 PM, 余长洪 wrote:
>
> I am reading the ‘Mahout in Action’
>
> I have installed mahout 0.9
>
> But when i run ‘bin/mahout cat donut.csv’ as the book say, i go
On Jun 13, 2014, at 6:04 PM, Yash Sharma wrote:
>
> > Hi, The donut.csv file you are looking for is present at -
> > ./examples/src/main/resources/donut.csv
> >
> > Peace,
> > Yash
> >
> >
> > On Fri, Jun 13, 2014 at 3:15 PM, 余长洪 wrote:
> >
&g
Hi Wei, Which similarity class are you using for the same?
On Mon, Aug 25, 2014 at 11:52 AM, Wei Li wrote:
> Hi Mahout users:
>
> We have tried the item-based CF recommender with a user_id, item_id,
> rating data. while the recommendation output is less than our expected, for
> example, if
Pearson Coefficient Similarity does not go very well with small datasets
with less similarities - and removes those from output. Since you are using
co-occurrence similarity this is not the case.
On Mon, Aug 25, 2014 at 2:11 PM, Peng Zhang wrote:
> If there are no suitable recommendations for a
Mahout collab filtering would remove the items you have already rated since
you would not want to see the same items which you have already used and
rated.
On Mon, Aug 25, 2014 at 2:14 PM, Wei Li wrote:
> OK, why not just output the items uses clicked or rated before? does it
> output the these
