semvec/pypi-packages huggingface dataset:
KNN_TextClassifier 0.0.0
KNN_TextClassifier
License: BSD

KNN_TextClassifier
------------------------------

KNN_TextClassifier


Sample Usage
````````````
.. code:: python

	>>> import KNN_TextClassifier
		#load random Data,Labels
	>>> dataMatrix,labels = KNN_TextClassifier.loadData(feature_num = 4,rows = 10)
		#norm Data reduce influence of high ranges
	>>> normDataSet = KNN_TextClassifier.norm(dataMatrix)

		#predict K should be odd to avoid voting result like {('A',2),('B',2)} difficult choice. 
		#Parameter format classify(testData,TrainData,TrainData_Labels,K) 
		'''
			testData and TrainData should be 2-D list. row represents a text data. Columns represent feature values.
			TrainData_Labels should be a list like ['A','B','C'] an element represents a row of TrainData's class.
			K should be odd as I said before.
		'''        
	>>> print KNN_TextClassifier.classify([[1,2,3,4],[2],[3]], dataMatrix, labels, K=3)
		['C', 'C', 'C']
    
		#predict
	>>> print KNN_TextClassifier.classify([['天气好','2','3','4'],['2'],['3']], dataMatrix, labels, K=3)
		['C', 'A', 'C']
    
		#get transformed vector
	>>> vector,vocabList = KNN_TextClassifier.word2VectorMatrix([['1','2','3','4'],['2'],['3']])
	>>> print vector
		[[ 1.  1.  1.  1.]
		[ 0.  0.  1.  0.]
		[ 0.  1.  0.  0.]]
    
		#get transformed vocabList
	>>> print vocabList
		['1', '3', '2', '4']

Installation 
```````````` 
.. code:: bash 

    $ pip install KNN_TextClassifier

Links 
````` 

* `Code on Github <https://github.com/ArnoldGaius/KNN_TextClassifier>`_
Yozuch 0.8.0
reStructuredText based static blog generator
License: BSD
Keywords: static blog generator reStructuredText

Yozuch
======
.. image:: https://travis-ci.org/akrylysov/yozuch.svg?branch=master
    :target: https://travis-ci.org/akrylysov/yozuch

Yozuch is a reStructuredText based static blog generator written in Python 3.

Documentation is available at http://yozuch.krylysov.com/.

Quick start
-----------

.. code-block:: bash

    pip3 install yozuch
    yozuch init myblog
    cd myblog
    yozuch serve

Open ``http://localhost:8000/`` in a browser to preview your blog.