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mirror of https://github.com/gsi-upm/sitc synced 2024-11-05 07:31:41 +00:00

Fixed broken link and bug of sklearn-deap with scikit 0.24

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cif2cif 2021-04-19 17:47:22 +02:00
parent b80c097362
commit c9114cc796

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@ -56,7 +56,7 @@
"metadata": {},
"source": [
"# Genetic Algorithms\n",
"In this section we are going to use the library DEAP [References](#References) for implementing a genetic algorithms.\n",
"In this section we are going to use the library DEAP [[References](#References)] for implementing a genetic algorithms.\n",
"\n",
"We are going to implement the OneMax problem as seen in class.\n",
"\n",
@ -200,11 +200,13 @@
"source": [
"## 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], 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"
"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 the version 0.24 of scikit. Just comment the different approaches."
]
},
{
@ -261,6 +263,15 @@
}
],
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@ -276,7 +287,7 @@
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