splitters/transformers

  else:

    print("NOTE: linkcode extension not found -- no links to source generated")

def linkcode_resolve(domain, info):

  """

  Determine the URL corresponding to Python object

Dataset

-------

The :code:`dc.data.Dataset` class is the abstract parent clss for all datasets. This class should never be directly initialized, but contains a number of useful method implementations.

The :code:`dc.data.Dataset` class is the abstract parent class for all

datasets. This class should never be directly initialized, but

contains a number of useful method implementations.

The goal of the :code:`Dataset` class is to be maximally interoperable with other common representations of machine learning datasets. For this reason we provide interconversion methods mapping from :code:`Dataset` objects to pandas dataframes, tensorflow Datasets, and PyTorch datasets.

What is DeepChem?

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

The DeepChem project aims to build high quality tools to democratize the use of deep learning in the sciences. The core `DeepChem Repo`_ serves as a monorepo that organizes the DeepChem suite of scientific tools. As the project matures, smaller more focused tool will be surfaced in more targeted repos.

The DeepChem project aims to build high quality tools to democratize

the use of deep learning in the sciences. The origin of DeepChem

focused on applications of deep learning to chemistry, but the project

has slowly evolved past its roots to broader applications of deep

learning to the sciences.

DeepChem is primarily developed in Python, but we are experimenting with adding support for other languages.

The core `DeepChem Repo`_ serves as a monorepo that organizes the DeepChem suite of scientific tools. As the project matures, smaller more focused tool will be surfaced in more targeted repos. DeepChem is primarily developed in Python, but we are experimenting with adding support for other languages.

What are some of the things you can use DeepChem to do? Here's a few examples:

- Predict physical properties of simple materials

- Analyze protein structures and extract useful descriptors

- Count the number of cells in a microscopy image

- More coming soon...

We should clarify one thing up front though. DeepChem is a machine

learning library, so it gives you the tools to solve each of the

applications mentioned above yourself. DeepChem may or may not have

prebaked models which can solve these problems out of the box.

Over time, we hope to grow the set of scientific applications DeepChem

can address. This means we need lots of help! If you're a scientist

who's interested in open source, please pitch on building DeepChem.

Quick Start

-----------

DeepChem with the one-liner

.. code-block:: bash

    conda install -y -c deepchem -c rdkit -c conda-forge -c omnia deepchem-gpu=2.3.0

Then open your python and try running.

That said, we would very much appreciate a citation if you find our tools useful. You can cite DeepChem with the following reference.

.. highlight:: guess

.. code-block:: guess

  @book{Ramsundar-et-al-2019,

      title={Deep Learning for the Life Sciences},

      author={Bharath Ramsundar and Peter Eastman and Patrick Walters and Vijay Pande and Karl Leswing and Zhenqin Wu},

.. _`on GitHub`: https://github.com/deepchem/deepchem

.. _`Gitter`: https://gitter.im/deepchem/Lobby

.. important:: Join our `community gitter <https://forms.gle/9TSdDYUgxYs8SA9e8>`_ to discuss DeepChem. Sign up for our `forums <https://forum.deepchem.io/>`_ to ralk about research, development, and general questions. 

.. important:: Join our `community gitter <https://forms.gle/9TSdDYUgxYs8SA9e8>`_ to discuss DeepChem. Sign up for our `forums <https://forum.deepchem.io/>`_ to talk about research, development, and general questions. 

.. toctree::

   :maxdepth: 4

   Datasets <datasets>

   Data Loaders <dataloaders>

   Featurizers <featurizers>

   Splitters <splitters>

   Transformers <transformers>

   Models <models>

   Introduction to Keras <keras>

DeepChem with the one-liner

.. code-block:: bash

    conda install -y -c deepchem -c rdkit -c conda-forge -c omnia deepchem-gpu=2.3.0

Then open your python and try running.

Splitters

=========

DeepChem :code:`dc.splits.Splitter` objects are a tool to meaningfully

split DeepChem datasets for machine learning testing. The core idea is

that when evaluating a machine learning model, it's useful to creating

training, validation and test splits of your source data. The training

split is used to train models, the validatation is used to benchmark

different model architectures. The test is ideally held out till the

very end when it's used to gauge a final estimate of the model's

performance.

The :code:`dc.splits` module contains a collection of scientifically

aware splitters. In many cases, we want to evaluate scientific deep

learning models more rigorously than standard deep models since we're

looking for the ability to generalize to new domains. Some of the

implemented splitters here may help.

Splitter

--------

The :code:`dc.splits.Splitter` class is the abstract parent class for

all splitters. This class should never be directly instantiated.

.. autoclass:: deepchem.splits.Splitter

  :members:

RandomSplitter

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

.. autoclass:: deepchem.splits.RandomSplitter

  :members:

IndexSplitter

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

.. autoclass:: deepchem.splits.IndexSplitter

  :members:

IndiceSplitter

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

.. autoclass:: deepchem.splits.IndiceSplitter

  :members:

SpecifiedSplitter

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

.. autoclass:: deepchem.splits.SpecifiedSplitter

  :members:

SpecifiedIndexSplitter

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

.. autoclass:: deepchem.splits.SpecifiedIndexSplitter

  :members:

RandomGroupSplitter

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

.. autoclass:: deepchem.splits.RandomGroupSplitter

  :members:

RandomStratifiedSplitter

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

.. autoclass:: deepchem.splits.RandomStratifiedSplitter

  :members:

SingletaskStratifiedSplitter

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

.. autoclass:: deepchem.splits.SingletaskStratifiedSplitter

  :members:

MolecularWeightSplitter

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

.. autoclass:: deepchem.splits.MolecularWeightSplitter

  :members:

MaxMinSplitter

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

.. autoclass:: deepchem.splits.MaxMinSplitter

  :members:

ButinaSplitter

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

.. autoclass:: deepchem.splits.ButinaSplitter

  :members:

ScaffoldSplitter

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

.. autoclass:: deepchem.splits.ScaffoldSplitter

  :members:

FingeprintSplitter

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

.. autoclass:: deepchem.splits.FingerprintSplitter

  :members:

TimeSplitterPDBbind

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

.. autoclass:: deepchem.splits.TimeSplitterPDBbind

  :members: