This week, I am working to get the dynamic time warping functionality into my program. The process of doing so includes re-processing the features to include the time series, putting each series back together when we construct sequences, and then performing the DTW to generate a number that will be used to compute the kNN of each sequence which can then be used for predictions with the models. The processing time of these activities has gone up significantly since we have been using five different metrics with each of the F phase datasets. I am returning to school next week, and once I've completed the DTW processing all that will remain before we put together our second paper (The date for the reach journal we would like to submit it to is October 1), I am hoping I will have time to look again into the Agglomerative Hierarchical Clustering concept, which I did not successfully complete when we explored it earlier in the summer and then changed focus to the paper. We heard back
This week, I finished up the graphs of Coefficient of Variability that Dr. Weeks had asked for and worked on calculating sleep onset latency and then the change in onset latency from night to night. Once I have these results, I want to apply this comparison to the different features that we've previously calculated (DAR, Longest Sleep Bout, etc.). I also am looking at the average stay of patients.
Going forward, we're going to work on classifying sleep features as positive or negative with the help of Dr. Weeks and Dr. Skornyakov and see what new challenges this approach presents.
Going forward, we're going to work on classifying sleep features as positive or negative with the help of Dr. Weeks and Dr. Skornyakov and see what new challenges this approach presents.
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