tag:github.com,2008:https://github.com/ArieRS/GeneticAlgorithmPython/releasesRelease notes from GeneticAlgorithmPython2020-12-05T23:29:23Ztag:github.com,2008:Repository/318933149/2.9.02020-12-05T23:29:23ZPyGAD 2.9.0<p>Changes in PyGAD 2.9.0 (06 December 2020):</p>
<ol>
<li>The fitness values of the initial population are considered in the <code>best_solutions_fitness</code> attribute.</li>
<li>An optional parameter named <code>save_best_solutions</code> is added. It defaults to <code>False</code>. When it is <code>True</code>, then the best solution after each generation is saved into an attribute named <code>best_solutions</code>. If <code>False</code>, then no solutions are saved and the <code>best_solutions</code> attribute will be empty.</li>
<li>Scattered crossover is supported. To use it, assign the <code>crossover_type</code> parameter the value <code>"scattered"</code>.</li>
<li>NumPy arrays are now supported by the <code>gene_space</code> parameter.</li>
<li>The following parameters (<code>gene_type</code>, <code>crossover_probability</code>, <code>mutation_probability</code>, <code>delay_after_gen</code>) can be assigned to a numeric value of any of these data types: <code>int</code>, <code>float</code>, <code>numpy.int</code>, <code>numpy.int8</code>, <code>numpy.int16</code>, <code>numpy.int32</code>, <code>numpy.int64</code>, <code>numpy.float</code>, <code>numpy.float16</code>, <code>numpy.float32</code>, or <code>numpy.float64</code>.</li>
</ol>ahmedfgadtag:github.com,2008:Repository/318933149/2.8.12020-10-03T03:53:38Z2.8.1: Bug fix in applying crossover<p>Bug fix in applying the crossover operation when the <code>crossover_probability</code> parameter is used.<br>
Thanks to Eng. Hamada Kassem, RA/TA, Construction Engineering and Management, Faculty of Engineering, Alexandria University, Egypt: <a href="https://www.linkedin.com/in/hamadakassem" rel="nofollow">https://www.linkedin.com/in/hamadakassem</a></p>ahmedfgadtag:github.com,2008:Repository/318933149/2.8.02020-09-20T21:49:13Z2.8.0<p>Train Keras models using PyGAD (pygad.kerasga)</p>ahmedfgadtag:github.com,2008:Repository/318933149/2.7.22020-09-14T16:49:47Z2.7.2<p>Add files via upload</p>ahmedfgadtag:github.com,2008:Repository/318933149/2.7.12020-09-14T16:49:47Z2.7.1<p>Add files via upload</p>ahmedfgadtag:github.com,2008:Repository/318933149/2.7.02020-09-11T18:03:47Z2.7.0<p>Add files via upload</p>ahmedfgadtag:github.com,2008:Repository/318933149/2.6.02020-08-06T13:42:11Z2.6.0<p>Add files via upload</p>ahmedfgadtag:github.com,2008:Repository/318933149/2.5.02020-07-19T19:42:45Z2.5.0<p>Add files via upload</p>ahmedfgadtag:github.com,2008:Repository/318933149/2.4.02020-07-05T17:08:22Z2.4.0<p>Add files via upload</p>ahmedfgadtag:github.com,2008:Repository/318933149/1.0.192020-05-04T14:50:56Z1.0.19: Update README.md<ul>
<li>More details about the project are added.</li>
<li>Documenting the init_rand_high and init_rand_high parameters.</li>
</ul>ahmedfgad