Logistic Regression with Gradient Ascent

Python script implementing a Logistic Regression machine learning algorithm for binary input/output data utilizing gradient ascent to develop values to predict future outcomes based on provided new data.

Implementation

This code requires a "training file" (check out 'example.csv') which needs to be in the format of lists/rows of binary data. The last value in the row represents the overall outcome/label of all previous entries/paramaters in the respective row. Once the training is complete, a testing file can be used to determine the level of precision in which the code can predict future outcomes based on given new data.

Notes

  • Coded in Python