*THIS IS A CONTINUATION TO MY ARTICLE HERE: LINK
Once I found the Top 50 features, I scaled everything down to achieve a higher accuracy with values being more alike. After scaling the data to a standard format, I conducted a test-train split. 75% of the data was used for the training data and the other remaining 25% become the test data.
I then performed a logistic regression and SVC to compare results. A classification report was used on each to verify results. The machine yielded adequate results between 96% and 97% in the slight favor of SVC. This suggests that it can predict the likelihood of a company going sinking to the bottom of the financial sea with more accuracy than logistic regression.