load model test.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "ce6b4b79",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pickle\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "9884f27f",
   "metadata": {},
   "outputs": [],
   "source": [
    "model = pickle.load(open('model.ml', 'rb'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "ded089c3",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/vivek/.local/lib/python3.8/site-packages/sklearn/base.py:441: UserWarning: X does not have valid feature names, but LogisticRegression was fitted with feature names\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array([0])"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "unseen = np.array([[10,101,76,48,180,32.9,0.171,63]])\n",
    "model.predict(unseen)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2e05359b",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}