method mean(scoresstddev(scoreslogreg = nn we have seen the accuracy for the different values of the regularization parameter with itwe can control the model complexitysimilar to the parameter for the nearest neighbor method smaller values for result in higher penaltythat isthey make the model more complex quick look at the bias-variance chart for our best candidatec shows that our model has high bias--test and train error curves approach closely but stay at unacceptably high values this indicates that logistic regression with the current feature space is under-fitting and cannot learn model that captures the data correctly so what nowwe switched the model and tuned it as much as we could with our current state of knowledgebut we still have no acceptable classifier it seems more and more that either the data is too noisy for this task or that our set of features is still not appropriate to discriminate the classes that are good enough