  A large proportion of online comments present on public domains are
constructive, however a significant proportion are toxic in nature. The
comments contain lot of typos which increases the number of features manifold,
making the ML model difficult to train. Considering the fact that the data
scientists spend approximately 80% of their time in collecting, cleaning and
organizing their data [1], we explored how much effort should we invest in the
preprocessing (transformation) of raw comments before feeding it to the
state-of-the-art classification models. With the help of four models on Jigsaw
toxic comment classification data, we demonstrated that the training of model
without any transformation produce relatively decent model. Applying even basic
transformations, in some cases, lead to worse performance and should be applied
with caution.

Computation and Language;Artificial Intelligence