Categorical Data yes/no to 0/1 python - is it a right approach?
Yes, in my opinion, encoding yes/no to 1/0 would be the right approach for you.
Python's sklearn requires features in numerical arrays.
There are various ways of encoding : Label Encoder; One Hot Encoder. etc
However, since your variable only has 2 levels of categories, it wouldnt make much difference if you go for LabelEncoder or OneHotEncoder.
My dataset has few features with yes/no (categorical data). Few of the machine learning algorithms that I am using, in python, do not handle categorical data directly. I know how to convert yes/no, to 0/1, but my question is -
Is this a right approach to go about it?
Can these values of no/yes to 0/1, be misinterpreted by algorithms ?
The algorithms I am planning to use for my dataset are - Decision Trees (DT), Random Forests (RF) and Neural Networks (NN).