diff options
Diffstat (limited to 'python-naive-bayes.spec')
| -rw-r--r-- | python-naive-bayes.spec | 219 |
1 files changed, 219 insertions, 0 deletions
diff --git a/python-naive-bayes.spec b/python-naive-bayes.spec new file mode 100644 index 0000000..5dfdb26 --- /dev/null +++ b/python-naive-bayes.spec @@ -0,0 +1,219 @@ +%global _empty_manifest_terminate_build 0 +Name: python-naive-bayes +Version: 0.1.1 +Release: 1 +Summary: Naive Bayes Text Classification +License: MIT +URL: https://github.com/itdxer/naive-bayes +Source0: https://mirrors.nju.edu.cn/pypi/web/packages/ab/aa/75158e517a7678485e9a748b3117ce5edb750af643b2a916b061ee53ba4d/naive-bayes-0.1.1.tar.gz +BuildArch: noarch + + +%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
+``` + +%package -n python3-naive-bayes +Summary: Naive Bayes Text Classification +Provides: python-naive-bayes +BuildRequires: python3-devel +BuildRequires: python3-setuptools +BuildRequires: python3-pip +%description -n python3-naive-bayes +# 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
+``` + +%package help +Summary: Development documents and examples for naive-bayes +Provides: python3-naive-bayes-doc +%description help +# 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
+``` + +%prep +%autosetup -n naive-bayes-0.1.1 + +%build +%py3_build + +%install +%py3_install +install -d -m755 %{buildroot}/%{_pkgdocdir} +if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi +if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi +if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi +if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi +pushd %{buildroot} +if [ -d usr/lib ]; then + find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst +fi +if [ -d usr/lib64 ]; then + find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst +fi +if [ -d usr/bin ]; then + find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst +fi +if [ -d usr/sbin ]; then + find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst +fi +touch doclist.lst +if [ -d usr/share/man ]; then + find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst +fi +popd +mv %{buildroot}/filelist.lst . +mv %{buildroot}/doclist.lst . + +%files -n python3-naive-bayes -f filelist.lst +%dir %{python3_sitelib}/* + +%files help -f doclist.lst +%{_docdir}/* + +%changelog +* Fri May 05 2023 Python_Bot <Python_Bot@openeuler.org> - 0.1.1-1 +- Package Spec generated |