Naive Bayes Text Classification
Project description
# Naive Bayes Text Classifier
Text classifier based on Naive Bayes.
## Instalation
```bash
$ pip install naive-bayes
```
## Usage example
```python
from naivebayes import NaiveBayesTextClassifier
classifier = NaiveBayesTextClassifier(
categories=categories_list,
stop_words=stopwords_list
)
classifier.train(train_docs, train_classes)
predicted_classes = classifier.classify(test_docs)
```
`NaiveBayesTextClassifier` is a simple wrapper around `scikit-learn` class `CountVectorizer`. You can put all arguments which support this class. For more information please check `scikit-learn` official documentation.
## More examples
Check examples at `examples` folder. Before run them, install requirements in this folder.
Clone repository from github
```bash
$ git clone git@github.com:itdxer/naive-bayes.git
$ cd naive-bayes/examples
$ pip install -r requirements.txt
```
And run some example
### Usenet 20 newsgroup
```bash
$ python 20newsgroup
```
### Kaggle IMDB reviews competition
```bash
$ python imdb_reviews
```
Text classifier based on Naive Bayes.
## Instalation
```bash
$ pip install naive-bayes
```
## Usage example
```python
from naivebayes import NaiveBayesTextClassifier
classifier = NaiveBayesTextClassifier(
categories=categories_list,
stop_words=stopwords_list
)
classifier.train(train_docs, train_classes)
predicted_classes = classifier.classify(test_docs)
```
`NaiveBayesTextClassifier` is a simple wrapper around `scikit-learn` class `CountVectorizer`. You can put all arguments which support this class. For more information please check `scikit-learn` official documentation.
## More examples
Check examples at `examples` folder. Before run them, install requirements in this folder.
Clone repository from github
```bash
$ git clone git@github.com:itdxer/naive-bayes.git
$ cd naive-bayes/examples
$ pip install -r requirements.txt
```
And run some example
### Usenet 20 newsgroup
```bash
$ python 20newsgroup
```
### Kaggle IMDB reviews competition
```bash
$ python imdb_reviews
```
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