Older blog entries for sness (starting at number 4702)

Snowpatch QuickStart Guide | WestGrid

Snowpatch QuickStart Guide | WestGrid: "Here is an example of a script to run an MPI program, pn, using 6 processors (3 nodes with 2 processors per node). If the script file is named pn.pbs, submit the job with qsub pn.pbs.

#PBS -l procs=6

# Script for running MPI sample program pn on SnowPatch


echo "Current working directory is `pwd`"

echo "Running on hosts:"

echo "Starting run at: `date`"

mpiexec -n $PBS_NCPUS ./pn

echo "Job finished at: `date`"

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Syndicated 2012-12-05 21:50:00 from sness

Salmon Run: Learning Mahout : Classification

Salmon Run: Learning Mahout : Classification: "The following code uses the AdaptiveLogisticRegression algorithm (which runs multiple SGD algorithms and automatically chooses the best one) to classify the 20 Newsgroups training set, then test the algorithm with the 20 Newsgroups test set. The code demonstrates the building of feature vectors for each document using multiple hashing encoders."

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Syndicated 2012-12-05 21:06:00 from sness

MpichCluster - Community Ubuntu Documentation

MpichCluster - Community Ubuntu Documentation: "You should now see output similar to this:

Hello from processor 0 of 8
Hello from processor 1 of 8
Hello from processor 2 of 8
Hello from processor 3 of 8
Hello from processor 4 of 8
Hello from processor 5 of 8
Hello from processor 6 of 8
Hello from processor 7 of 8"

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Syndicated 2012-12-05 19:39:00 from sness

George Dyson - President's Distinguished Lecture - Honorary Doctor of Laws - University of Victoria

George Dyson - President's Distinguished Lecture - Honorary Doctor of Laws - University of Victoria: "Date: Tuesday, December 4, 2012 (7:00 pm)
Location: University Centre Farquhar Auditorium
Ticket Information: Free admission and everyone welcome. Tickets must be reserved in advance. For ticket inquiries call 250-721-8480 or visit auditorium.uvic.ca."

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Syndicated 2012-12-04 17:27:00 from sness


Seattle: "Seattle makes the power of Cloud Computing available to everyone. It's free, community driven, open source, and provides access to computers worldwide.

Seattle operates on resources such as laptops, servers, and phones, which are donated by users and institutions. The global distribution of the Seattle network provides the ability to use it in application contexts that include cloud computing, peer-to-peer networking, ubiquitous/mobile computing, and distributed systems."

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Syndicated 2012-12-01 20:11:00 from sness

RepyTutorial – Seattle

RepyTutorial – Seattle: "This guide provides an introduction to using the Repy sandbox environment. It describes what restrictions are placed upon the sandboxed code with examples. At the end of reading this document you should be able to write Repy programs, manage the restrictions on programs, and understand whether Repy is appropriate for a specific task or program.

It is assumed that you have a basic understanding of network programming such as socket, ports, IP addresses, and etc. Also, a basic understanding of HTML is useful but not required. Lastly, you need a basic understanding of the Python programming language. If not, you might want to first read through the Python tutorial at  http://www.python.org/doc/ or the python tutorial in this site. You do not need to be a Python expert to use Repy, but as Repy is a subset of Python, being able to write a simple Python program is essential.


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Syndicated 2012-12-01 20:10:00 from sness

Newton Institute Seminar : van Houwelingen, JC, 17/06/2008

Newton Institute Seminar : van Houwelingen, JC, 17/06/2008: "Global testing of association and/or predictability in regression problems with p>>n predictors"

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Syndicated 2012-12-01 01:02:00 from sness

Logistic Regression

Logistic Regression: "Logistic Regression (SGD)
Logistic regression is a model used for prediction of the probability of occurrence of an event. It makes use of several predictor variables that may be either numerical or categories.

Logistic regression is the standard industry workhorse that underlies many production fraud detection and advertising quality and targeting products. The Mahout implementation uses Stochastic Gradient Descent (SGD) to all large training sets to be used.

For a more detailed analysis of the approach, have a look at the thesis of Paul Komarek:


See MAHOUT-228 for the main JIRA issue for SGD.


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Syndicated 2012-12-01 00:59:00 from sness


Logistic: "
In order to find the matrix B for which L is minimised, a Quasi-Newton Method is used to search for the optimized values of the m*(k-1) variables. Note that before we use the optimization procedure, we 'squeeze' the matrix B into a m*(k-1) vector. For details of the optimization procedure, please check weka.core.Optimization class.

Although original Logistic Regression does not deal with instance weights, we modify the algorithm a little bit to handle the instance weights.

For more information see:

le Cessie, S., van Houwelingen, J.C. (1992). Ridge Estimators in Logistic Regression. Applied Statistics. 41(1):191-201."

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Syndicated 2012-12-01 00:59:00 from sness

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