from sklearn.metrics import accuracy_score, precision_score, recall_score, f1_score from sklearn.model_selection import train_test_split from sklearn.linear_model import LogisticRegression import nltk from nltk.corpus import movie_reviews # Load movie reviews dataset nltk.download('movie_reviews') ...
[ ] movie_reviews... Sentiment Polarity Dataset Version 2.0 [ ] mte_teip5... MULTEXT-East 1984 annotated corpus 4.0 [ ] mwa_ppdb... The monolingual word aligner (Sultan et al. 2015) subset of the Paraphrase Database. [ ] names... Names Corpus, Version 1.3 (1994-03-29) [ ] nom...
# 需要导入模块: import nltk [as 别名]# 或者: from nltk importsentiment[as 别名]defdemo_movie_reviews(trainer, n_instances=None, output=None):""" Train classifier on all instances of the Movie Reviews dataset. The corpus has been preprocessed using the default sentence tokenizer and WordPunct...
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示例1: category_by_movie ▲点赞 9▼ defcategory_by_movie():fromnltk.corpusimportmovie_reviewsasmrfromnltkimportFreqDistfromnltkimportNaiveBayesClassifierfromnltkimportclassifyfromnltk.corpusimportnamesfromnltk.classifyimportapply_featuresimportrandom
Related Tutorials: Natural Language Processing With Python's NLTK Package Natural Language Processing With spaCy in Python Use Sentiment Analysis With Python to Classify Movie Reviews Split Your Dataset With scikit-learn's train_test_split() Logging in Python Remove...
[ ] movie_reviews... Sentiment Polarity Dataset Version 2.0 [ ] mte_teip5... MULTEXT-East 1984 annotated corpus 4.0 [ ] mwa_ppdb... The monolingual word aligner (Sultan et al. 2015) subset of the Paraphrase Database. [ ] names... Names Corpus, Version...
If you want to learn how to apply NLP to real-world data, including TED talks, articles, and movie reviews, using Python libraries and frameworks, including NLTK, scikit-learn, spaCy, and SpeechRecognition, check out the resources below: Introduction to Natural Language Processing in Python Natu...
<package id="movie_reviews" name="Sentiment Polarity Dataset Version 2.0" author="Bo Pang and Lillian Lee" copyright="Copyright (C) 2004 Bo Pang and Lillian Lee" webpage="http://www.cs.cornell.edu/people/pabo/movie-review-data/" license="Creative Commons Attribution 4.0 International" licens...