Pick several nouns and/or verbs from your previous assignment. Create a column in the dataframe that indicates if that line from t

 The project requires building of a NLP classifiers and sentiment analysis based on the below guidelines. I have attached the Rmarkdown file and required input files for the analysis. please use Python to do the below steps preferably. The 'cleaned_subtitles' will be the dataset used for the analysis and 'movie reviews' file is what you should use for sentiment analysis

Classifcation:

– Pick several nouns and/or verbs from your previous assignment. Create a column in the dataframe that indicates if that line from the movie/TV show includes that word or does not include that word. You can use 0 and 1 or any labels that make sense to you. Remember, we covered regular expression detection and deletion in the raw text assignments! - Once you have created this column, use string replacement to delete that word from your subtitles. We will take the word out to see if we can predict when it is used – if you leave it in, it's a perfect predictor! - Use *two* feature extraction methods and *two* machine learning algorithms to determine if you can predict when your noun or verb will be used. You should include four different classification reports below. 

Sentiment:

– Use *one* of the unsupervised lexicon techniques to create sentiment scores for your movie/TV show. - What is the overall sentiment of your movie/TV show? How would you interpret the scores provided? - Using the movie reviews mini dataset provided online, create a sentiment tagging model (one feature extraction method + one algorithm). - With this new model, create sentiment scores for your movie/TV show. - What is the overall sentiment using the new model of sentiment tagging? How would you interpret the scores provided? 

Place your order
(550 words)

Approximate price: $22

Calculate the price of your order

550 words
We'll send you the first draft for approval by September 11, 2018 at 10:52 AM
Total price:
$26
The price is based on these factors:
Academic level
Number of pages
Urgency
Basic features
  • Free title page and bibliography
  • Unlimited revisions
  • Plagiarism-free guarantee
  • Money-back guarantee
  • 24/7 support
On-demand options
  • Writer’s samples
  • Part-by-part delivery
  • Overnight delivery
  • Copies of used sources
  • Expert Proofreading
Paper format
  • 275 words per page
  • 12 pt Arial/Times New Roman
  • Double line spacing
  • Any citation style (APA, MLA, Chicago/Turabian, Harvard)

Our guarantees

Delivering a high-quality product at a reasonable price is not enough anymore.
That’s why we have developed 5 beneficial guarantees that will make your experience with our service enjoyable, easy, and safe.

Money-back guarantee

You have to be 100% sure of the quality of your product to give a money-back guarantee. This describes us perfectly. Make sure that this guarantee is totally transparent.

Read more

Zero-plagiarism guarantee

Each paper is composed from scratch, according to your instructions. It is then checked by our plagiarism-detection software. There is no gap where plagiarism could squeeze in.

Read more

Free-revision policy

Thanks to our free revisions, there is no way for you to be unsatisfied. We will work on your paper until you are completely happy with the result.

Read more

Privacy policy

Your email is safe, as we store it according to international data protection rules. Your bank details are secure, as we use only reliable payment systems.

Read more

Fair-cooperation guarantee

By sending us your money, you buy the service we provide. Check out our terms and conditions if you prefer business talks to be laid out in official language.

Read more