This will compare PCA and TSNE in a sequential neural net and evaluate the score for each
reduction algorithm.
Without dimensionality reduction:
- evaluation score = 0.66
- PCA score = 0.77
- TSNE score = 0.70
Looking at the table below there is already a baseline of predicting 65% zeros, so the real
question is whether or not this can predict a one (diabetic). Further analysis needs to be done
to answer this question and I plan on running a random forest classifier to see if it produces better
results.
1 | 0 | Total | |
---|---|---|---|
y | 268 | 500 | 768 |
% | 35% | 65% | 100% |
There will also be a plot.ly diagram coming showing the labeled data in 3d space.
Any and all advice/insights are welcome!
Thanks!