Hi, I did not understand one thing. You said in your earlier tutorials, lemmatization is better than porter stemmer, then why you are using porter stemmer.? is there any specific reason .?
Glad you asked. Stemmer operates on a single word without knowledge of the context, and can't discriminate between words which have different meanings depending on part of speech. However, Stemmers are typically easier to implement and run faster, and the reduced accuracy may not matter for some applications like in our case. It would be a good exercise for you to use different things, and compare final results.
but the main question is how to use these bigrams for text classification. The matrix created is sparse . So cant directly fit the dataframe directly using some Machine learning algorithm... Can you please silver lining here
AMAZING THANK YOU SO MUCH
Great tutorials with clear explanation..why is the vectorization implemented without tokenization ?
I need help in Text summarizer. Do you have any video on this topic?
Hi, I did not understand one thing. You said in your earlier tutorials, lemmatization is better than porter stemmer, then why you are using porter stemmer.? is there any specific reason .?
Glad you asked.
Stemmer operates on a single word without knowledge of the context, and can't discriminate between words which have different meanings depending on part of speech. However, Stemmers are typically easier to implement and run faster, and the reduced accuracy may not matter for some applications like in our case.
It would be a good exercise for you to use different things, and compare final results.
@@KnowledgeCenter Thank you for replying and clarifying my doubt.
Hi, can you please explain how to apply k smoothing, add one k, and how to find probability of the next word. please
Great
Thanks.
but the main question is how to use these bigrams for text classification.
The matrix created is sparse . So cant directly fit the dataframe directly using some Machine learning algorithm...
Can you please silver lining here
how to convert number of web page into vector form
while fitting my data in fit_tranform method it is showing that:'list' object has no attribute 'lower'
please help🙂
Did you get a solution to that?
I need source code of this video plz