Movie Review Analysis
An analysis of the
movie_review data set included in the
nltk corpus. I would probably add some buzz words here later on.
- What is in this repo
- Running it
- Legal stuff
What is in this repo
- An implementation of
nltk.NaiveBayesClassifiertrained against 5000 movie reviews. Implemented in
- Naive Bayes:
- Linear Model
- Naive Bayes:
- Implemented a voting system to choose the best out of all the learning methods. Implemented in
After that you can do
$ conda update conda $ conda install scikit-learn nltk
Downloading the dataset
The dataset used in this package is bundled along with the
Run your python interpreter
>>> import nltk >>> nltk.download('stopwords') >>> nltk.download('movie_reviews')
NOTE: You can check system specific installation instructions from the official
Check if everything is good till now by running your interpreter again and importing these
>>> import nltk >>> from nltk.corpus import stopwords, movie_reviews >>> import sklearn >>>
If these imports work for you. Then you are good to go!
- Clone the repo
$ git clone https://github.com/prodicus/movieReviewsAnalysis $ cd movieReviewsAnalysis ## run the ipython server $ ipython notebook
Order of running
"So what, Well this is pretty basic!"
Yes, it is but hey we all do start somewhere right?
Psst. I am working on a spam filtering system. You know the one in which you paste an email and then it tells you whether it is a spam or not.
You can follow me on twitter @tasdikrahman to keep tabs on it.
You can find a copy of the License at http://prodicus.mit-license.org/