Build a text classifier on the IMDB sentiment classification dataset, you can use any classification method,...

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Build a text classifier on the IMDB sentiment classification dataset, you can use any classification method, but you must training your model on the first 40000 instances and testing your model on the last 10000 instances. Your code should include: 1: Read the file, incorporate the instances into the training set and testing set. 2: Pre-processing the text, you can choose whether you need stemming, removing stop words, removing non-alphabetical words. (Not all classification models need this step, it is OK if you think your model can perform better without this step, and you can give some justification in the report.) Build a text classifier on the IMDB sentiment classification dataset, you can use any classification method, but you must training your model on the first 40000 instances and testing your model on the last 10000 instances. Your code should include: 1: Read the file, incorporate the instances into the training set and testing set. 2: Pre-processing the text, you can choose whether you need stemming, removing stop words, removing non-alphabetical words. (Not all classification models need this step, it is OK if you think your model can perform better without this step, and you can give some justification in the report.)

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