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*Delegated Augi to work on building the training data.
*Started to work on the classifier by studying machine learning models
*Edited words.txt with new words and remove words that i don't think help with the classification. Removed: march/ Added: rundown, list, mentors, overview, graduating, company, founders, autumn.
*The new words.txt had increased the accuracy from 0.76 to 0.83 in the first run
*The accuracy really fluctuated. Got as low as 0.74 but the highest run has been 0.866
*Note: testing inside of KyranGoogleClassifier instead of the main folder because the main folder was testing out the new improved crawler.
*It also seemed that rundown and autumn is the least important with 0.0 score so I removed them
2018-06-28:
