collect-results.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Collect results\n",
    "\n",
    "Have a look to see what model performed best."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import orchest"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = orchest.get_inputs()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "linear-regression-rmse         0.7330332386117091\n",
      "\n",
      "decision-tree-regressor-rmse   0.7121161026219296\n",
      "\n",
      "svm-regressor-rmse             0.6854343614613364\n"
     ]
    }
   ],
   "source": [
    "for name, value in data.items():\n",
    "    if name != \"unnamed\":\n",
    "        print(f\"\\n{name:30} {value}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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