semvec/pypi-packages huggingface dataset:
sklearn-deltatfidf 0.1
DeltaTfidfVectorizer for scikit-learn
License: MIT
Keywords: sklearn,scikit-learn,tfidf,deltatfidf,delta tfidf

=================
sklearn-deltatfidf
=================

DeltaTfidfVectorizer for scikit-learn.

The Delta TFIDF is suggested in a article_ by Justin Martineau and Tim Finin, and usually associated with sentiment classification or polarity detection of text.

Usage
-----

.. code:: python

  from sklearn_deltatfidf import DeltaTfidfVectorizer

  v = DeltaTfidfVectorizer()
  data = ['word1 word2', 'word2', 'word2 word3', 'word4']
  labels = [1, -1, -1, 1]
  v.fit_transform(data, labels)

  # you can use it in pipelines as usual
  pipe = Pipeline([
        ('vectorizer', DeltaTfidfVectorizer()),
        ('clf', svm.LinearSVC())
    ])
  pipe.fit(data, labels)

Installation
------------

With ``pip``:

.. code-block:: console

    $ pip install sklearn-deltatfidf

From source:

.. code-block:: console

    $ git clone https://github.com/r-m-n/sklearn-deltatfidf.git
    $ cd sklearn-deltatfidf
    $ python setup.py install

.. _article: http://ebiquity.umbc.edu/_file_directory_/papers/446.pdf
voicelabs 0.0.10
VoiceInsights Python SDK
License: MIT
Keywords: voicelabs,voiceinsights,alexasdk

--------------------
--------------------

# Install the package

you can install the package locally in the current folder by using the following command:

#from test PIP repo
pip install -t ./ -i https://testpypi.python.org/pypi VoiceInsights

#from main public PIP repo
pip install -t ./ VoiceInsights

--------------------
--------------------

## SDK usage:


from voicelabs import  VoiceInsights

appToken = '<YOUR APP TOKEN>'   
vi = VoiceInsights()

def on_session_started(session_started_request, session):
    # Called when the session starts """   
    vi.initialize(appToken, session)

def on_intent(intent_request, session):
    intent = intent_request['intent']
    intent_name = intent_request['intent']['name']

    response = None
    #Logic to populate response goes here

    #invoke SDK track method like follows
    vi.track(intent_name, intent_request, response)

    return response


--------------------
--------------------