{
"cells": [
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"## Autoencoder transformation (encode-decode)\n",
"\n",
"Considering a dataset with $p$ numerical attributes. \n",
"\n",
"The goal of the autoencoder is to reduce the dimension of $p$ to $k$, such that these $k$ attributes are enough to recompose the original $p$ attributes. However from the $k$ dimensionals the data is returned back to $p$ dimensions. The higher the quality of autoencoder the similiar is the output from the input. "
]
},
{
"cell_type": "code",
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"metadata": {},
"outputs": [
{
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"text": [
"── \u001b[1mAttaching core tidyverse packages\u001b[22m ──────────────────────────────────────────────────────────────── tidyverse 2.0.0 ──\n",
"\u001b[32m✔\u001b[39m \u001b[34mdplyr \u001b[39m 1.1.4 \u001b[32m✔\u001b[39m \u001b[34mreadr \u001b[39m 2.1.5\n",
"\u001b[32m✔\u001b[39m \u001b[34mforcats \u001b[39m 1.0.0 \u001b[32m✔\u001b[39m \u001b[34mstringr \u001b[39m 1.5.1\n",
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"\u001b[32m✔\u001b[39m \u001b[34mlubridate\u001b[39m 1.9.3 \u001b[32m✔\u001b[39m \u001b[34mtidyr \u001b[39m 1.3.1\n",
"\u001b[32m✔\u001b[39m \u001b[34mpurrr \u001b[39m 1.0.2 \n",
"── \u001b[1mConflicts\u001b[22m ────────────────────────────────────────────────────────────────────────────────── tidyverse_conflicts() ──\n",
"\u001b[31m✖\u001b[39m \u001b[34mpurrr\u001b[39m::\u001b[32m%||%()\u001b[39m masks \u001b[34mbase\u001b[39m::%||%()\n",
"\u001b[31m✖\u001b[39m \u001b[34mdplyr\u001b[39m::\u001b[32mfilter()\u001b[39m masks \u001b[34mstats\u001b[39m::filter()\n",
"\u001b[31m✖\u001b[39m \u001b[34mdplyr\u001b[39m::\u001b[32mlag()\u001b[39m masks \u001b[34mstats\u001b[39m::lag()\n",
"\u001b[36mℹ\u001b[39m Use the conflicted package (\u001b[3m\u001b[34m