January 2007
Monthly Archive
Data Mining Models
Posted by Edison Macabebe on 22 Jan 2007 | Tagged as: Data Mining
Intoducing the DM Learners
This article details how basic data-mining machine learners are built. These learners are the One Rule, Decision Tree, Naïve Bayes and Prism. Additional tips are also provided in how to process the training and test data.
All codes were written using the Java language utilizing Sun’s latest tool as of this writing, under the brand name of JDK 5.0. To author the codes more efficiently, conveniently and professionally, I chose to use Netbeans latest IDE version 4.0.
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Computing Performance of Symmetric Multi-Processing Scheduling
Posted by Bobby Corpus on 21 Jan 2007 | Tagged as: Performance
You might have noticed that when you do a transaction in a bank, you usually see a single line being served by 2 or more tellers. You must have perceived that this technique of lining up customers is better than when each teller has its own line. This will lessen the chance of you being stuck for a long time when the guy before you takes a long time to complete transaction.
In computer systems, you can view the customers as tasks to be executed by 2 or more processors. Each processor will pick from a common line, a task that it will execute. In this article, we will analyze the performance of symmetric multiprocessing using continuous markov chain analysis. We will also be using the tool available from www.extremecomputing.org to help us compute the probabilities.
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The MVC (Model-View-Controller)
Posted by Aurelio Pascual on 08 Jan 2007 | Tagged as: J2EE
The second installment in our series on Design Patterns is the most popular ofall patterns, the MVC. MVC stands for Model-View-Controller. That means your application is separated into these three components. Let us discuss these components one by one.
- Model – a model is a representation of your business logic and/or data. For example, if you have an online shopping application, your shopping cart, items, and the codes that update your cart are the models.
- Controller – takes user input and decides what to do with the model.
- View – the one responsible for the presentation of the state of the model.
One good analogy for the MVC is a car. The model is the car engine. The brakes, steering wheel and other controls represent the controller. The tachometerand the thermometer are the views.
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Computing Continuous Markov Chains Using Extreme Optimal Solver
Posted by Bobby Corpus on 04 Jan 2007 | Tagged as: Performance
In the last article, we computed the probabilities associated with the states in a continuous markov chain model using balance equations. The computation, although elementary, was tedious and distracts us from the real problem, which is understanding the performance of a queueing model. Fortunately, there is an online tool we can use in order to speed up the computation of continuous markov chains. This tool can be found in the site http://www.extremecomputing.org. This site contains numerous solvers that can be of interest to the computational scientists. However, the tool we are interested in is the Continuous Markov Chain solver which can be accessed in this link.
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