Regie Felix


Oct 2, 2013 (4 years and 9 months ago)


Regie Felix, B.S. Bioinformatics at CSUSB

Machine Learning Research for the Center of Bio
Image Informatics in UC Santa Barbara

Mentor: Nazli Dereli

Private Investigator: Dr. Ambuj Singh

Time Series Analysis and Machine Learning Techniques on
Various Datasets

Time series is a sequence of data that is

taken in consistent time intervals.

One is able to analyze
trends within the data and use them to predict what will happen in the future. This process is
called time series analysis, which consist
s of three steps: preprocessing, analysis, and
checking. We analyzed a dataset that expressed the amount of air passengers from 1949 to 1960

and developed a
model that
illustrated the fluctuations of the
Another type of
is categorizing the data via time series classification. Machine learning techniques, such
as decision trees and artificial neural networks, are used for this type of classification.

For this
analysis, we used a UCI KDD dataset of EEG sensor values of 20 p
atients (10 alcoholic and 10
alcoholics) while they were looking at three different stimuli: one picture, two pictures that
two pictures that do not match. Our goal was to correctly classify the data so that by
just the EEG results, the mode
l would be able to predict the status of the patient.

Our accuracy
for both decision trees and ANN were low at first; we then tried revised our project by trying
different sensors, increasing the number of data points, and different classifiers.

ification project on
going; we are still trying more machine learning techniques to increase
the accuracy of our model.