Print out performance metrics for existing Sentiment Analysis (Python) program
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Post a project like this2399
€20(approx. $21)
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Description
Experience Level: Entry
General information for the business: Python program for Sentiment Analysis
Kind of development: Customization of existing program
Description of requirements/functionality: An existing Python program uses Word2Vec and Random Forest classifier to appoint sentiment to tweets. I would like additional code to produce Accuracy, Precision, Recall and F1 score for the system, similar to code @ http://zablo.net/blog/post/twitter-sentiment-analysis-python-scikit-word2vec-nltk-xgboost.
Would like printout as below:
=================== Results ===================
F1 0.38949672
Precision 0.45408163
Recall 0.34099617
Accuracy 0.579594345421
Specific technologies required: Python
OS requirements: Windows
Extra notes: A Python program - Twitter-Sentiment-Analysis.py (attached) uses train and test data (attached) and utilises Word2Vec to produce features that are classified using Random Forest classifier. Additional few lines of code are required to produce metrics - Accuracy, Precision, Recall and F1 score.
Kind of development: Customization of existing program
Description of requirements/functionality: An existing Python program uses Word2Vec and Random Forest classifier to appoint sentiment to tweets. I would like additional code to produce Accuracy, Precision, Recall and F1 score for the system, similar to code @ http://zablo.net/blog/post/twitter-sentiment-analysis-python-scikit-word2vec-nltk-xgboost.
Would like printout as below:
=================== Results ===================
F1 0.38949672
Precision 0.45408163
Recall 0.34099617
Accuracy 0.579594345421
Specific technologies required: Python
OS requirements: Windows
Extra notes: A Python program - Twitter-Sentiment-Analysis.py (attached) uses train and test data (attached) and utilises Word2Vec to produce features that are classified using Random Forest classifier. Additional few lines of code are required to produce metrics - Accuracy, Precision, Recall and F1 score.
Eddy S.
93% (17)Projects Completed
17
Freelancers worked with
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Projects awarded
90%
Last project
3 May 2022
United States
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