SSH-Master-Thesis/ethan_data_processing_scripts

Using classifier.py

The train(classifications: int, data: list, results: list, testdata: list, testresults: list) function should be used.

Data and Testdata should be arrays of arrays of features, ex:

Suppose there are 3 features, each a float from 0 to 1. Data could be: [[.3, .2, .3], [.3, .3, .3], [.3, .4, .5]...]

Results should be ints in an array, each result accoring to the list of features it should represent the classification of.

Plan for classifier.py

Make a command line utility that reads in samples, transforms them to FeatureVectors and then runs a number of classifications on them.