My Biodata

Siew Wei's Biodata (GM05156)




WHO AM I ?




Someone who’s a Squash freak
Yes I love to play squash and I use to challenge others =)

Someone who loves nutrition & always believe it can leave a positive impact to the society
I dream to be a “food doctor” (although I’m only a nutritionist), to help people live a healthy lifestyle.

Someone who likes exam but also don’t believe in exam
I do like exam because it induces me to read the book and I get to learn something new!
But I don’t believe getting good marks in exam will guarantee success in your career!

Someone who enjoys & appreciates new experiences
I appreciate what I’ve learned in the class, and the friends I know throughout the whole course.

In short, Siew Wei always has this slogan in life: "Whenever Siew Wei wants to do something, she will surely make it"



Tuesday, February 25, 2014

Lecture# 5 (Part 1) Crystal Ball, Clairvoyant, Fortune Telling ... Can Predictive Analytic Deliver the Future ?





Question 1:

Many predictive analytic models are based on neural network technologies. What is the role of neural networks in predictive analytics? How can neural networks help predict the likelihood of future events. In answering these questions, specifically reference Blue Cross Blue Shield of Tennessee.

The role of the neural networks can act as replacement for analysts in retail, manufacturing and many other industries use a variety of statistical methods to solve a range of problems in forecasting, data classification and pattern recognition and produce forecasts as accurate as or better than those available from other statistical methods. In fact, neural networks offer many advantages, including: improved accuracy over traditional statistical methods; a unified approach to a wide variety of predictive analytics problems; and they requires fewer statistical assumptions and can manage complex predictive analytics tasks in a more automated way, which saves time for analysts and programmers
The likelihood of future events in neural networks are assisted by the fact that they can learn to adjust to new circumstances, lend themselves to parallel processing, function without having all the information or having that information in a structured format, copy with huge amounts to data with different variables, and analyze relationships found in the data Blue Cross Blue Shield of Tennessee has a neural network which they use to predict health resources that will be needed after certain procedures. The patterns they find can help determine if a patient will have a reaction to the procedure. Having this data quickly can help save health care costs and patients.

Question 2:

What if the Richmond police began to add demographic data to its predictive analytics system to further attempt to determine the type of person (by demographic) who would commit a crime. Is predicting the type of person who would commit a crime by demographic data (ethnicity, gender, income level, and so on) good or bad?

It is not a issue of good or bad to add demographic data to its predictive analytics system to further attempt to determine the type of person (by demographic) who would commit a crime by demographic data. The main issue here is whether there is any infringement of privacy law or whether the person who use the predictive system will use it in a proper manner but not to abuse it. 
Question 3:

In the movie Gattaca, predictive analytics were used to determine the most successful career for a person. Based on DNA information, the system determined whether or not an individual was able to advance through an education track to become something like an engineer or if a person should complete only a lower level of education and become a janitor. The government then acted on the system’s recommendations and placed people in various career tracks. Is this good or bad use of technology? How is this different from the variety of personal test you can take that informs you of your aptitude for different career?

 In my opinion, this is a bad use of technology by acted according to the system recommendation.  This is because everyone has different potential which yet to be displayed. We can not simply determine a future of a person by relying on a predictive system. 


The personal test is served as a reference for someone to know about the best suit career for them.  Basically it is no much different from the predictive system because it is also based on the data collected and recommend a best option to a person.
Question 4: What role can geographic information system (GISs) play in the use of predictive analytics? As you answer this question, specifically reference FedEx’s use of predictive analytics to:

(1)    Determine which customers will respond negatively to a price increase and

(2)    Project additional revenues from proposed drop-box locations.


A geographic information system (GIS) integrates hardware, software, and data for capturing, managing, analyzing, and displaying all forms of geographically referenced information. GIS allows us to view, understand, question, interpret, and visualize data in many ways that reveal relationships, patterns, and trends in the form of maps, globes, reports, and charts.  A GIS will helps us answer questions and solve problems by looking at our data in a way that is quickly understood and easily shared. GIS technology can be integrated into any enterprise information system framework.
 By using a GIS, FedEx can know whether their sales increase or drop in a particular area. When a price increase in  a particular area, the sale will usually drop and FedEx can trace the complains from customer regarding the price from a particular region. 


When a particular area has a high sales volume, FedEx can estimate more sale base on GIS. FedEx may increase the production from a particular area to generate additional revenue. 

Question 5:

The department of Defense (DoD) and the Pacific Northwest National Laboratory are combining predictive analytics with visualization technologies to predict the probability that a terrorist attack will occur. For example, suspected terrorists caught on security cameras who loiter too long in a given place might signal their intent to carry out terrorist attack. How can this type of predictive analytics be used in airport? At what other buildings and structures might this be used?



Predictive analytics is a way of using “Big Data” techniques to predict possible outcomes, from results of presidential elections to the behavior of individual people. Depending on the application, predictive analytic data often includes demographic information, family and marital status, purchasing history, past weather patterns, business transaction histories, social media activity, website clicks, and, of course, telephone metadata, all of which help shape the map of an possible underlying reality.


The same concept can be adopted here. The data of the criminal can be share in the airport and the data of a criminal such as which area of that particular criminal likelihood to appear and the travel data of the criminal to be shared in the system in the airport. When the CCTV detected the person, the security in the airport may be alarmed to be more alert.
This method can be used in anywhere and any building so long as the system properly installed and operated.  

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