- This package provides the Python “pyneurgen” module, which contains several
classes for implementing grammatical evolution, a form of genetic programming, and classes for neural networks. These classes enable the creation of hybrid models that can embody the strengths of grammatical evolution and neural networks.
While neural networks can be adept at solving non-linear problems, some problems remain beyond reach. For example, a difficult search space can cause suboptimal solutions to be reached. Also, multiobjective problems become extremely difficult, if not impossible. With genetic algorithms, a more thorough search can be made.
Metadata
Release files for pyneurgen 0.3.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| pyneurgen-0.3.1.tar.gz | 581.4 kB | Without provenance | Details for pyneurgen-0.3.1.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| pyneurgen-0.3.1-py2.7.egg | Legacy Egg format | - | - | Details for pyneurgen-0.3.1-py2.7.egg |
Total release size: 679.5 kB
Release files / pyneurgen-0.3.1.tar.gz
| Download URL | pyneurgen-0.3.1.tar.gz |
|---|---|
| Size | 581.4 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
511b50f9039e40cbd65ea60a210761030d6ad3518eccde451d264991a99fe2a9
|
|
BLAKE2b-256 checksum How to use checksums |
df3a21a7d310c3acb28c9a26b0a78a6b52d7ee00294ad19f65735dd4e8a6a887
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
Release files / pyneurgen-0.3.1-py2.7.egg
| Download URL | pyneurgen-0.3.1-py2.7.egg |
|---|---|
| Size | 98.1 kB |
| Tags | Egg |
|
SHA-256 checksum How to use checksums |
6f05980bd6f210a637381f626ad7a488f2d57d611b607bc4e19d0256516ce48a
|
|
BLAKE2b-256 checksum How to use checksums |
98a5aacad6fa27e81e2c082424f91b6ef382cb12a9097425f8faa17bc873925f
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
Security for pyneurgen 0.3.1
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.