I have a dataset on which I need to apply binary classification to predict target value. I applied 5 algorithms on training set such as Logistic regression, Naive Bayes, KNN, SVM, Decision Trees. Out of which Binary Classification using Logistic Regression is giving me highest accuracy but the thing is I did not preprocess my dataset. Now should I again train my model using all five algorithms or Is it sure that Binary Classification using Logistic Regression will again give my highest accuracy after pre processing training dataset?
No one can tell you if the results will be different after pre-processing, since we don't know what pre-processing you will be doing. But best practices are to pre-process that dataset uniformly so that all algorithms are being trained on the same data.