Metadata-Version: 2.1
Name: deeptl
Version: 0.0.0
Summary: Deep Topological Learning: a deep learning library for complex topological tasks.
Home-page: https://github.com/pietrobarbiero/deep-topological-learning
Maintainer: P. Barbiero
Maintainer-email: barbiero@tutanota.com
License: Apache 2.0
Download-URL: https://github.com/pietrobarbiero/deep-topological-learning.git
Description: Deep Topological Learning (DTL)
        ======================================================
        
        DTL is a Python package providing an easy-to-use software
        for learning complex topologies with neural networks.
        
        DTL networks are based on a novel theory (`the duality theory`)
        bridging
        two research fields which are usually thought as disjointed:
        supervised deep learning and unsupervised competitive
        neighborhood-based learning.
        
        
        Using DTL
        -----------
        
        .. code:: python
        
            from deeptl import DeepTopologicalClustering
        
            X, y = load_iris(return_X_y=True)
        
            # load and fit the neural model
            model = DeepTopologicalClustering()
            model.fit(X, N=40, num_epochs=400, lr=0.0008)
        
            # compute the final graphs
            model.compute_sample_graph()
            model.compute_graph()
        
            # plot the results
            model.plot_adjacency_matrix()
            model.plot_graph(y)
            model.plot_sample_graph(y)
        
        
        
        .. image:: example.png
            :width: 200px
            :align: center
            :height: 200px
            :alt: result
        
        
        Authors
        -------
        
        `Pietro Barbiero <http://www.pietrobarbiero.eu/>`__
        
        Licence
        -------
        
        Copyright 2020 Pietro Barbiero.
        
        Licensed under the Apache License, Version 2.0 (the "License"); you may
        not use this file except in compliance with the License. You may obtain
        a copy of the License at: http://www.apache.org/licenses/LICENSE-2.0.
        
        Unless required by applicable law or agreed to in writing, software
        distributed under the License is distributed on an "AS IS" BASIS,
        WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
        
        See the License for the specific language governing permissions and
        limitations under the License.
Platform: UNKNOWN
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved
Classifier: Programming Language :: Python
Classifier: Topic :: Software Development
Classifier: Topic :: Scientific/Engineering
Classifier: Operating System :: Microsoft :: Windows
Classifier: Operating System :: POSIX
Classifier: Operating System :: Unix
Classifier: Operating System :: MacOS
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Description-Content-Type: text/x-rst
Provides-Extra: tests
Provides-Extra: docs
