I have twitter data which is labelled with the sentiment(Postive, Negative, Neutral) and I have evaluated the performance of Tf-Idf and Doc2Vec feature extractor using the KNN algorithm and logistic regression.
The output for using KNN is
From the above output, I could see that TF-IDF is better than Doc2Vec in logistic regression and Doc2Vec is better than TF-IDF in KNN. Then in KNN, TF-IDF is performing poorly because of recall score.
Is there any way that one can say which feature exactor is better based on the above output and what is the meaning if TF-IDF has high precision but poor recall score. I need some conclusion based on the above output. Any insight is much appreciated. Thanks in advance!