2. cross-validation using traing and testing data set
3. word vectorization with TFIDf
4. attribute reduction with fuzzy-rough quick reduct algorithm
5. Fuzzy rough nearest neighbour algorithm(FRNN) for the classification of tweets to three classes of positive - 1, negative - 0 and neutral - 2.
5. Need the confusion matrix, precision, recall, f1-score, support and accuracy
6. Classify another data set using the developed classifier as whether the tweets are positive, negative or neutral (This is expecting to change the label value in the csv file under the label column)
7. Need all the reports and comments where necessary in the code
8. Do the project in Python using jupyter notebook
I attached the labeled data set to build and test the classifier and data set to be classified separetely","employmentType":["FULL_TIME","PART_TIME","CONTRACTOR","TEMPORARY","PER_DIEM"],"jobLocationType":"TELECOMMUTE","hiringOrganization":{"@type":"Organization","name":"Toogit","sameAs":"https://www.toogit.com/","logo":"https://www.toogit.com/images/toogit_logo_initial.png"},"identifier":{"@type":"PropertyValue","name":"Toogit","value":362488},"skills":["Data Analysis","Machine Learning","Natural Language Toolkit (NLTK)","Pandas","Scikit-Learn"],"applicantLocationRequirements":[{"@type":"Country","name":"IN"},{"@type":"Country","name":"Canada"},{"@type":"Country","name":"USA"},{"@type":"Country","name":"Germany"},{"@type":"Country","name":"Pakistan"},{"@type":"Country","name":"Philippines"},{"@type":"Country","name":"Indonesia"},{"@type":"Country","name":"Sri Lanka"},{"@type":"Country","name":"Nigeria"},{"@type":"Country","name":"China"},{"@type":"Country","name":"Russia"},{"@type":"Country","name":"Bangladesh"}],"validThrough":"2024-07-30T12:10:35+05:30","url":"https://www.toogit.com/freelance-jobs/MzYyNDg4"}
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