Creating a DML cookbook sounds very useful ... especially for new data
scientists starting to pick up DML. It shows vectorization avoiding loops,
and people are familiar with the semantics. There may be more nuggets like
that throughout the DML algorithms. And the list will grow in the course
of time.
Regards,
Berthold Reinwald
IBM Almaden Research Center
office: (408) 927 2208; T/L: 457 2208
email: reinwald@us.ibm.com
From: Shirish Tatikonda <shirish.tatikonda@gmail.com>
To: dev@systemml.incubator.apache.org
Date: 12/16/2015 10:03 PM
Subject: Re: DML example on main SystemML website
Deron,
Along with such a complete algorithm, we could also include one/two common
and useful DML snippets. We could also create a "DML Cookbook" with such
snippets and keep adding more over time.
Some example snippets are below  note that I created them quite a while
back, and they may need revision and testing.
*Classifier Performance*
# Confusion matrix
cm = table(truthLabels, predictedLabels)
TP = as.scalar(cm[1,1])
TN = as.scalar(cm[2,2])
FP = as.scalar(cm[1,2])
FN = as.scalar(cm[2,1])
accuracy = (TP+TN)/nrow(truthLabels)
precision = TP / (TP+FP)
recall = TP / (TP+FN)
print("Accuracy = " + accuracy + ", Precision = " + precision + ", Recall
=
" + recall);
*Covariance matrix*
A = read("input.mtx");
N = nrow(A);
# column means
mu = colSums(A)/N;
# Covarianace matrix
C = (t(A) %*% A)/(N1)  (N/(N1))*t(mu) %*% mu;
*Select rows satisfying a predicate*
ind = diag(ppred(A[,1], thresh, ">"));
ind = removeEmpty(target=ind, margin="rows");
result = ind %*% A;
*Center and Scale columns*
A = read("input.mtx");
cm = colMeans(A);
cvars = (colSums (A^2));
cvars = (cvars  N*(cm^2))/(N1);
Ascaled = (Acm)/sqrt(cvars);
*Random shuffling of rows*
N = nrow(A);
s = sample(N, N, replace=FALSE);
tab = table(seq(1:N), s);
result = tab %*% A;
On Wed, Dec 16, 2015 at 5:59 PM, Deron Eriksson <deroneriksson@gmail.com>
wrote:
> That example is perfect. Concise and powerful. Thank you Fred.
>
> Deron
>
>
> On Wed, Dec 16, 2015 at 4:16 PM, Frederick R Reiss <frreiss@us.ibm.com>
> wrote:
>
> > We can use the Poisson nonnegative matrix factorization example from
last
> > week's webcast:
> >
> > i = 0
> > while(i < max_iterations) {
> > H = (H * (t(W) %*% (V/(W%*%H + epsilon)))) / t(colSums(W))
> > W = (W * ((V/(W%*%H) + epsilon) %*% t(H))) / t(rowSums(H))
> > i = i + 1;
> > }
> >
> >
> > Sound ok to everyone?
> >
> > Fred
> >
> >
> > [image: Inactive hide details for Deron Eriksson 12/16/2015
04:02:26
> > PMHi, I think the main SystemML website at http://systemml.i]Deron
> > Eriksson 12/16/2015 04:02:26 PMHi, I think the main SystemML
> website
> > at http://systemml.incubator.apache.org/
> >
> > From: Deron Eriksson <deroneriksson@gmail.com>
> > To: dev@systemml.incubator.apache.org
> > Date: 12/16/2015 04:02 PM
> > Subject: DML example on main SystemML website
> > 
> >
> >
> >
> > Hi,
> >
> > I think the main SystemML website at
> http://systemml.incubator.apache.org/
> > needs to be updated so that the DML example is an actual algorithm or
at
> > least a fragment of an algorithm.
> >
> > Does anyone have a recommendation for a short, concise example that
shows
> > the power of DML?
> >
> > Thanks!
> > Deron
> >
> >
> >
>
