python - How can i concatenate the TF weight from the lexical features along with vector resulting form replacing the words with their emotions?

Question

I have a labeled dataset(Arabic Tweets) and labeld Lexicon, I want to detect the emotion by machine learning algorithms.

I did the preprocessing step and other functions. just I want to apply these steps:

1. compute the TF scheme in order to obtain how frequently an expression (term, word) occurs in a document.

2. To incorporate the affective lexical features we check the presence of lexicon terms in the sentence and we obtain a vector that represents each emotional category (anger, fear, sadness, and joy).

3. Finally, to carry out the classification, the concatenation of the TF sentence representation and the word-based features are used as input to the different algorithms (SVM, LR, MLP, MultinomialNB).

how can I do these steps because I am a beginner in Sentiment analysis and python:

question from:https://stackoverflow.com/questions/65928388/how-can-i-concatenate-the-tf-weight-from-the-lexical-features-along-with-vector

Answer 1

Waitting for answers