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Update 2_5_1_Exercise.ipynb

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ml4/2_5_1_Exercise.ipynb
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@ -200,13 +200,15 @@
"source": [
"## Optional. Optimizing ML hyperparameters\n",
"\n",
"One of the applications of Genetic Algorithms is the optimization of ML hyperparameters. Previously we have used GridSearch from Scikit. Using (sklearn-deap)[[References](#References)], optimize the Titatic hyperparameters using both GridSearch and Genetic Algorithms. \n",
"One of the applications of Genetic Algorithms is the optimization of ML hyperparameters. Previously, we have used GridSearch from Scikit. Using (sklearn-deap)[[References](#References)], optimize the Titatic hyperparameters using both GridSearch and Genetic Algorithms. \n",
"\n",
"The same exercise (using the digits dataset) can be found in this [notebook](https://github.com/rsteca/sklearn-deap/blob/master/test.ipynb).\n",
"\n",
"Submit a notebook where you include well-crafted conclusions about the exercises, discussing the pros and cons of using genetic algorithms for this purpose.\n",
"\n",
"Note: There is a problem with Scikit version 0.24. Comment on the different approaches."
"Note: There is a problem with Scikit version 0.24. Comment on the different approaches.",
"\n",
"You can also use the library (sklearn-genetic-opt)[https://sklearn-genetic-opt.readthedocs.io/en/stable/index.html]"
]
},
{
@ -256,7 +258,7 @@
"cell_type": "markdown",
"metadata": {},
"source": [
"The notebook is freely licensed under under the [Creative Commons Attribution Share-Alike license](https://creativecommons.org/licenses/by/2.0/). \n",
"The notebook is freely licensed under the [Creative Commons Attribution Share-Alike license](https://creativecommons.org/licenses/by/2.0/). \n",
"\n",
"© Carlos A. Iglesias, Universidad Politécnica de Madrid."
]