My dataset contains about 29 features with 3 class labels as result. Among these 29 features around 24 features are categorical i cannot transform each category into numbers as there are many more than 30+ categories in some features.
What i did is label Encoding.As my whole dataframe is encoded with label encoder how would i do prediction on it as i dont know what numbers have been used by the labelencoder for the data. Also what if a end user inputs a category which is not already present in the dataframe and has not been encoded earlier?
from sklearn import preprocessing le = preprocessing.LabelEncoder() data=data.apply(le.fit_transform)
This code has encoded my dataframe into numbers Now what should i do if i want to either print a particular category in its numeric transformed digit? Should i use label encoder or any other technique as i have applied Random Forest on my dataset.