fixes #3

[Addi-11]

Studied and compared the performance of various classification models, on the eeg dataset when split into different ratio of training to testing samples.

• Tabulised various evaluation metrics like:

  • precision
  • recall
  • accuracy
  • f1_score, for gaussian, svm, kneighbours, decison tree, logistic, random forest classification models.
    

• visualised the result using graphs.