libuplift.datasets.Lazada
=========================

.. py:module:: libuplift.datasets.Lazada

.. autoapi-nested-parse::

   Lazada E-comerce dataset.

   See https://github.com/kailiang-zhong/DESCN/tree/main/data/Lazada_dataset/ for details.

   ..
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Functions
---------

.. autoapisummary::

   libuplift.datasets.Lazada.fetch_Lazada


Module Contents
---------------

.. py:function:: fetch_Lazada(version='test', data_home=None, download_if_missing=True, random_state=None, shuffle=False, categ_as_strings=False, return_X_y=False, as_frame=False)

   
   Load the Lazada e-comerce dataset.

   Download it if necessary.

   There is a training and test set available.  The test dataset
   comes from a randomized experiment, in the training set assignment
   is biased.

   Details of the dataset can be found in the following paper:
   https://arxiv.org/pdf/2207.09920.

   The license is available `here <https://github.com/jszymon/uplift_sklearn_data/releases/download/Lazada/Lazada_LICENSE>`__

   :Parameters:

       **version** : string, optional
           Specify whether to return training ('train') or testing
           ('test') dataset.  Test dataset comes from a randomized
           experiment, in the training set assignment is biased.

       **data_home** : string, optional
           Specify another download and cache folder for the datasets. By default
           all scikit-learn data is stored in '~/scikit_learn_data' subfolders.

       **download_if_missing** : boolean, default=True
           If False, raise a IOError if the data is not locally available
           instead of trying to download the data from the source site.

       **random_state** : int, RandomState instance or None (default)
           Determines random number generation for dataset shuffling. Pass an int
           for reproducible output across multiple function calls.

       **shuffle** : bool, default=False
           Whether to shuffle dataset.

       **categ_as_strings** : bool, default=False
           Whether to return categorical variables as strings.

       **return_X_y** : boolean, default=False.
           If True, returns ``(data.data, data.target)`` instead of a Bunch
           object.

       **as_frame** : boolean, default=False
           If True features are returned as pandas DataFrame.  If False
           features are returned as object or float array.  Float array
           is returned if all features are floats.



   :Returns:

       **dataset** : dict-like object with the following attributes:
           ..

       **dataset.data** : numpy array
           Each row corresponds to the features in the dataset.

       **dataset.target_visit** : numpy array
           Each value is 1 if website visit occurred 0 otherwise.

       **dataset.target_conversion** : numpy array
           Each value is 1 if purchase occurred 0 otherwise.

       **dataset.target_spend** : numpy array
           Each value corresponds to the amount of money spent.

       **dataset.DESCR** : string
           Description of the Hillstrom dataset.

       **(data, target_conversion, target_visit, target_exposure)** : tuple if
           ``return_X_y`` is True











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