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DIGITS-CNN/cars/confusions.ipynb

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added 256 node FCs, confusion matrix notebook
2021-04-10 16:56:01 +01:00
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
add data augmentation script
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"id": "34b0345b",
added 256 node FCs, confusion matrix notebook
2021-04-10 16:56:01 +01:00
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
"import pandas as pd\n",
"import seaborn as sns\n",
"import matplotlib as mpl\n",
"from matplotlib import pyplot as plt"
]
},
{
"cell_type": "markdown",
add data augmentation script
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"id": "75b9f701",
added 256 node FCs, confusion matrix notebook
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"metadata": {},
"source": [
"# Render Confusion Matrices\n",
"\n",
"DIGITs generates confusion matrix tables, need to render as is, not generate using scikit-learn's func"
]
},
{
"cell_type": "code",
"execution_count": 2,
add data augmentation script
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"id": "10521209",
added 256 node FCs, confusion matrix notebook
2021-04-10 16:56:01 +01:00
"metadata": {},
"outputs": [],
"source": [
"frame = pd.read_csv('architecture-investigations/fc/3-layers/1024/conf.csv', index_col=0)\n",
"accuracy_col = frame.pop('Per-class accuracy')"
]
},
{
"cell_type": "code",
add data augmentation script
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"execution_count": 19,
"id": "02c2844f",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"50.0% 0.5\n",
"25.0% 0.25\n",
"30.0% 0.3\n",
"100.0% 1.0\n",
"71.43% 0.7142857142857143\n",
"44.44% 0.4444444444444444\n",
"62.5% 0.625\n",
"0.0% 0.0\n",
"50.0% 0.5\n",
"20.0% 0.2\n",
"\n",
"MAP = 49.3%\n"
]
}
],
"source": [
"normalised_array = np.ndarray((196, 196))\n",
"for idx, row in enumerate(frame.to_numpy()):\n",
" normalised_array[idx, :] = row / np.sum(row)\n",
"\n",
"# check correct accuracy\n",
"for acc, (idx, row) in zip(accuracy_col, enumerate(normalised_array[:10])):\n",
" print(acc, row[idx])\n",
"\n",
"class_acc_counter = 0\n",
"for idx, row in enumerate(normalised_array):\n",
" class_acc_counter += row[idx]\n",
" \n",
"print(f\"\\nMAP = {class_acc_counter*100/196:.4}%\")"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "91132579",
added 256 node FCs, confusion matrix notebook
2021-04-10 16:56:01 +01:00
"metadata": {},
"outputs": [
{
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" <th>Volvo XC90 SUV 2007</th>\n",
" <td>0</td>\n",
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" <td>0</td>\n",
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],
"text/plain": [
" AM General Hummer SUV 2000 \\\n",
"AM General Hummer SUV 2000 6 \n",
"Acura RL Sedan 2012 0 \n",
"Acura TL Sedan 2012 0 \n",
"Acura TL Type-S 2008 0 \n",
"Acura TSX Sedan 2012 0 \n",
"... ... \n",
"Volkswagen Beetle Hatchback 2012 0 \n",
"Volvo C30 Hatchback 2012 0 \n",
"Volvo 240 Sedan 1993 0 \n",
"Volvo XC90 SUV 2007 0 \n",
"smart fortwo Convertible 2012 0 \n",
"\n",
" Acura RL Sedan 2012 Acura TL Sedan 2012 \\\n",
"AM General Hummer SUV 2000 0 0 \n",
"Acura RL Sedan 2012 2 1 \n",
"Acura TL Sedan 2012 1 3 \n",
"Acura TL Type-S 2008 0 0 \n",
"Acura TSX Sedan 2012 1 0 \n",
"... ... ... \n",
"Volkswagen Beetle Hatchback 2012 0 0 \n",
"Volvo C30 Hatchback 2012 0 0 \n",
"Volvo 240 Sedan 1993 0 0 \n",
"Volvo XC90 SUV 2007 0 0 \n",
"smart fortwo Convertible 2012 0 0 \n",
"\n",
" Acura TL Type-S 2008 Acura TSX Sedan 2012 \\\n",
"AM General Hummer SUV 2000 0 0 \n",
"Acura RL Sedan 2012 0 2 \n",
"Acura TL Sedan 2012 0 2 \n",
"Acura TL Type-S 2008 3 0 \n",
"Acura TSX Sedan 2012 0 5 \n",
"... ... ... \n",
"Volkswagen Beetle Hatchback 2012 0 0 \n",
"Volvo C30 Hatchback 2012 0 0 \n",
"Volvo 240 Sedan 1993 0 0 \n",
"Volvo XC90 SUV 2007 0 0 \n",
"smart fortwo Convertible 2012 0 0 \n",
"\n",
" Acura Integra Type R 2001 \\\n",
"AM General Hummer SUV 2000 0 \n",
"Acura RL Sedan 2012 0 \n",
"Acura TL Sedan 2012 0 \n",
"Acura TL Type-S 2008 0 \n",
"Acura TSX Sedan 2012 0 \n",
"... ... \n",
"Volkswagen Beetle Hatchback 2012 0 \n",
"Volvo C30 Hatchback 2012 0 \n",
"Volvo 240 Sedan 1993 0 \n",
"Volvo XC90 SUV 2007 0 \n",
"smart fortwo Convertible 2012 0 \n",
"\n",
" Acura ZDX Hatchback 2012 \\\n",
"AM General Hummer SUV 2000 0 \n",
"Acura RL Sedan 2012 0 \n",
"Acura TL Sedan 2012 0 \n",
"Acura TL Type-S 2008 0 \n",
"Acura TSX Sedan 2012 0 \n",
"... ... \n",
"Volkswagen Beetle Hatchback 2012 0 \n",
"Volvo C30 Hatchback 2012 0 \n",
"Volvo 240 Sedan 1993 0 \n",
"Volvo XC90 SUV 2007 0 \n",
"smart fortwo Convertible 2012 0 \n",
"\n",
" Aston Martin V8 Vantage Convertible 2012 \\\n",
"AM General Hummer SUV 2000 0 \n",
"Acura RL Sedan 2012 0 \n",
"Acura TL Sedan 2012 0 \n",
"Acura TL Type-S 2008 0 \n",
"Acura TSX Sedan 2012 0 \n",
"... ... \n",
"Volkswagen Beetle Hatchback 2012 0 \n",
"Volvo C30 Hatchback 2012 0 \n",
"Volvo 240 Sedan 1993 0 \n",
"Volvo XC90 SUV 2007 0 \n",
"smart fortwo Convertible 2012 0 \n",
"\n",
" Aston Martin V8 Vantage Coupe 2012 \\\n",
"AM General Hummer SUV 2000 0 \n",
"Acura RL Sedan 2012 0 \n",
"Acura TL Sedan 2012 0 \n",
"Acura TL Type-S 2008 0 \n",
"Acura TSX Sedan 2012 0 \n",
"... ... \n",
"Volkswagen Beetle Hatchback 2012 0 \n",
"Volvo C30 Hatchback 2012 0 \n",
"Volvo 240 Sedan 1993 0 \n",
"Volvo XC90 SUV 2007 0 \n",
"smart fortwo Convertible 2012 0 \n",
"\n",
" Aston Martin Virage Convertible 2012 ... \\\n",
"AM General Hummer SUV 2000 0 ... \n",
"Acura RL Sedan 2012 0 ... \n",
"Acura TL Sedan 2012 0 ... \n",
"Acura TL Type-S 2008 0 ... \n",
"Acura TSX Sedan 2012 0 ... \n",
"... ... ... \n",
"Volkswagen Beetle Hatchback 2012 0 ... \n",
"Volvo C30 Hatchback 2012 0 ... \n",
"Volvo 240 Sedan 1993 0 ... \n",
"Volvo XC90 SUV 2007 0 ... \n",
"smart fortwo Convertible 2012 0 ... \n",
"\n",
" Toyota Camry Sedan 2012 \\\n",
"AM General Hummer SUV 2000 0 \n",
"Acura RL Sedan 2012 0 \n",
"Acura TL Sedan 2012 0 \n",
"Acura TL Type-S 2008 0 \n",
"Acura TSX Sedan 2012 0 \n",
"... ... \n",
"Volkswagen Beetle Hatchback 2012 0 \n",
"Volvo C30 Hatchback 2012 0 \n",
"Volvo 240 Sedan 1993 0 \n",
"Volvo XC90 SUV 2007 0 \n",
"smart fortwo Convertible 2012 0 \n",
"\n",
" Toyota Corolla Sedan 2012 \\\n",
"AM General Hummer SUV 2000 0 \n",
"Acura RL Sedan 2012 0 \n",
"Acura TL Sedan 2012 0 \n",
"Acura TL Type-S 2008 0 \n",
"Acura TSX Sedan 2012 0 \n",
"... ... \n",
"Volkswagen Beetle Hatchback 2012 0 \n",
"Volvo C30 Hatchback 2012 0 \n",
"Volvo 240 Sedan 1993 0 \n",
"Volvo XC90 SUV 2007 0 \n",
"smart fortwo Convertible 2012 0 \n",
"\n",
" Toyota 4Runner SUV 2012 \\\n",
"AM General Hummer SUV 2000 0 \n",
"Acura RL Sedan 2012 0 \n",
"Acura TL Sedan 2012 0 \n",
"Acura TL Type-S 2008 0 \n",
"Acura TSX Sedan 2012 0 \n",
"... ... \n",
"Volkswagen Beetle Hatchback 2012 0 \n",
"Volvo C30 Hatchback 2012 0 \n",
"Volvo 240 Sedan 1993 0 \n",
"Volvo XC90 SUV 2007 0 \n",
"smart fortwo Convertible 2012 0 \n",
"\n",
" Volkswagen Golf Hatchback 2012 \\\n",
"AM General Hummer SUV 2000 0 \n",
"Acura RL Sedan 2012 0 \n",
"Acura TL Sedan 2012 0 \n",
"Acura TL Type-S 2008 0 \n",
"Acura TSX Sedan 2012 0 \n",
"... ... \n",
"Volkswagen Beetle Hatchback 2012 0 \n",
"Volvo C30 Hatchback 2012 0 \n",
"Volvo 240 Sedan 1993 0 \n",
"Volvo XC90 SUV 2007 0 \n",
"smart fortwo Convertible 2012 0 \n",
"\n",
" Volkswagen Golf Hatchback 1991 \\\n",
"AM General Hummer SUV 2000 0 \n",
"Acura RL Sedan 2012 0 \n",
"Acura TL Sedan 2012 0 \n",
"Acura TL Type-S 2008 0 \n",
"Acura TSX Sedan 2012 0 \n",
"... ... \n",
"Volkswagen Beetle Hatchback 2012 0 \n",
"Volvo C30 Hatchback 2012 0 \n",
"Volvo 240 Sedan 1993 0 \n",
"Volvo XC90 SUV 2007 0 \n",
"smart fortwo Convertible 2012 0 \n",
"\n",
" Volkswagen Beetle Hatchback 2012 \\\n",
"AM General Hummer SUV 2000 0 \n",
"Acura RL Sedan 2012 0 \n",
"Acura TL Sedan 2012 0 \n",
"Acura TL Type-S 2008 0 \n",
"Acura TSX Sedan 2012 0 \n",
"... ... \n",
"Volkswagen Beetle Hatchback 2012 5 \n",
"Volvo C30 Hatchback 2012 1 \n",
"Volvo 240 Sedan 1993 0 \n",
"Volvo XC90 SUV 2007 0 \n",
"smart fortwo Convertible 2012 0 \n",
"\n",
" Volvo C30 Hatchback 2012 \\\n",
"AM General Hummer SUV 2000 0 \n",
"Acura RL Sedan 2012 0 \n",
"Acura TL Sedan 2012 0 \n",
"Acura TL Type-S 2008 0 \n",
"Acura TSX Sedan 2012 0 \n",
"... ... \n",
"Volkswagen Beetle Hatchback 2012 0 \n",
"Volvo C30 Hatchback 2012 4 \n",
"Volvo 240 Sedan 1993 0 \n",
"Volvo XC90 SUV 2007 0 \n",
"smart fortwo Convertible 2012 0 \n",
"\n",
" Volvo 240 Sedan 1993 Volvo XC90 SUV 2007 \\\n",
"AM General Hummer SUV 2000 0 0 \n",
"Acura RL Sedan 2012 0 0 \n",
"Acura TL Sedan 2012 0 0 \n",
"Acura TL Type-S 2008 0 0 \n",
"Acura TSX Sedan 2012 0 0 \n",
"... ... ... \n",
"Volkswagen Beetle Hatchback 2012 0 0 \n",
"Volvo C30 Hatchback 2012 0 0 \n",
"Volvo 240 Sedan 1993 10 0 \n",
"Volvo XC90 SUV 2007 0 7 \n",
"smart fortwo Convertible 2012 0 0 \n",
"\n",
" smart fortwo Convertible 2012 \n",
"AM General Hummer SUV 2000 1 \n",
"Acura RL Sedan 2012 0 \n",
"Acura TL Sedan 2012 0 \n",
"Acura TL Type-S 2008 0 \n",
"Acura TSX Sedan 2012 0 \n",
"... ... \n",
"Volkswagen Beetle Hatchback 2012 0 \n",
"Volvo C30 Hatchback 2012 0 \n",
"Volvo 240 Sedan 1993 0 \n",
"Volvo XC90 SUV 2007 0 \n",
"smart fortwo Convertible 2012 10 \n",
"\n",
"[196 rows x 196 columns]"
]
},
add data augmentation script
2021-04-16 23:59:20 +01:00
"execution_count": 4,
added 256 node FCs, confusion matrix notebook
2021-04-10 16:56:01 +01:00
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"frame"
]
},
{
"cell_type": "code",
add data augmentation script
2021-04-16 23:59:20 +01:00
"execution_count": 14,
"id": "72eacc1e",
added 256 node FCs, confusion matrix notebook
2021-04-10 16:56:01 +01:00
"metadata": {},
"outputs": [
{
"data": {
add data augmentation script
2021-04-16 23:59:20 +01:00
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAkcAAAJSCAYAAADJWGHfAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjQuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/Z1A+gAAAACXBIWXMAAAsTAAALEwEAmpwYAAA00UlEQVR4nO3df5AcZ33n8c9Xu0hYRrItBJJXsizrJ0ic2cMyWimEKPZdbAxXRuUqfogjwIVT4CBXUZILPw5iHH7kuLqcCAkBBAGTBAE+cyLEuGywXa4cZ62RdLVRkIxkSUi2tJJsYfxTRvLsPvfHTPc8Ws3s9Mz09M/3q0qlZ3t7pr/T80zPs99vdz/mnBMAAACqpqQdAAAAQJYwOAIAAPAwOAIAAPAwOAIAAPAwOAIAAPAwOAIAAPAwOAIQKzO7wMz+0cyeMrP/1cXzvMPMfhhnbGkxs183s31pxwEgGuM+R0A5mdkGSX8g6RWSnpE0IunTzrkfd/m875T0e5LWOucq3caZdWbmJC11zh1IOxYA8SBzBJSQmf2BpM9J+oykOZIWSPprSTfG8PSXS9pfhoFRFGbWn3YMANrD4AgoGTO7SNKfSvqAc+5/O+eec8694Jz7R+fcf6mtM83MPmdmo7V/nzOzabXfrTOzo2b2h2b2mJkdN7P31H53i6Q/kfRWM3vWzH7HzD5hZn/vbX+hmblg0GBm7zazQ2b2jJn93Mze4S3/sfe4tWa2o1au22Fma73f3W9mnzSz/1t7nh+a2ewmrz+I/4+9+N9sZjeY2X4ze8LMPuqt/1oz225mT9bW/Sszm1r73T/VVvvn2ut9q/f8HzKzE5K+HiyrPWZxbRuvqf08YGaPm9m6bt5XAPFhcASUzxpJL5a0bZJ1/qukIUmDkl4t6bWSPub9fq6kiyTNk/Q7kr5gZpc4525WNRv1HefcS5xzfzNZIGZ2oaTPS3qDc26GpLWqlvcmrjdL0g9q675U0v+U9AMze6m32gZJ75H0cklTJf3RJJueq+o+mKfqYO4rkv69pKsk/bqkj5vZFbV1xyRtkjRb1X13raT/JEnOudfX1nl17fV+x3v+Wapm0Tb6G3bOHZT0IUl/b2bTJX1d0jecc/dPEi+ABDE4AsrnpZJOtSh7vUPSnzrnHnPOPS7pFknv9H7/Qu33Lzjn7pT0rKTlHcYzLulVZnaBc+64c25Pg3XeKOlh59zfOecqzrlvSfqZpH/nrfN159x+59zzkm5TdWDXzAuqnl/1gqRvqzrw+Qvn3DO17e9VdVAo59wu59xwbbuHJX1Z0m9EeE03O+fO1OI5h3PuK5IOSHpQ0qWqDkYBZASDI6B8fiFpdotzYQYkHfF+PlJbFj7HhMHVaUkvaTcQ59xzkt4q6X2SjpvZD8zsFRHiCWKa5/18oo14fuGcG6u1g8HLSe/3zwePN7NlZnaHmZ0ws6dVzYw1LNl5HnfO/arFOl+R9CpJf+mcO9NiXQAJYnAElM92SWckvXmSdUZVLQkFFtSWdeI5SdO9n+f6v3TO3e2c+7eqZlB+puqgoVU8QUzHOoypHV9UNa6lzrmZkj4qyVo8ZtLLgM3sJaqeEP83kj5RKxsCyAgGR0DJOOeeUvU8my/UTkSebmYvMrM3mNl/r632LUkfM7OX1U5s/hNJf9/sOVsYkfR6M1tQOxn8I8EvzGyOmd1YO/fojKrlufEGz3GnpGVmtsHM+s3srZJWSLqjw5jaMUPS05KerWW13j/h9yclLWrzOf9C0k7n3HtVPZfqS11HCSA2DI6AEnLO/bmq9zj6mKTHJT0q6YOSvldb5VOSdkraLelfJP2/2rJOtvUjSd+pPdcunTugmVKLY1TSE6qeyzNx8CHn3C8kvUnSH6paFvxjSW9yzp3qJKY2/ZGqJ3s/o2pW6zsTfv8JSd+oXc32llZPZmY3Srpe9df5B5JeE1ylByB93AQSAADAQ+YIAADAw+AIAADAw+AIAADAw+AIAADAw+AIAADAk4nBkZldb2b7zOyAmX047XiQLWZ22Mz+xcxGzGxnbdksM/uRmT1c+/+StONE8szsa7XJY3/qLWvYN6zq87XjzO5g4lcUX5N+8gkzO1Y7royY2Q3e7z5S6yf7zOy6dKJGmlIfHJlZn6QvSHqDqjd1e7uZrUg3KmTQbzrnBp1zq2o/f1jSvc65pZLurf2M8rlV1XsG+Zr1jTdIWlr7t1HVO1+jHG7V+f1EkjbXjiuDtTkCVfv+eZuklbXH/HXtewolkvrgSNXZvg845w45586qOgnkjSnHhOy7UdI3au1vaPKpMFBQzrl/UvXmkb5mfeNGSX/rqoYlXWxmlyYSKFLVpJ80c6Okb9cmDf65qhMEv7ZnwSGTsjA4mqfq3XkDR3XuZJKAk/RDM9tlZhtry+Y4547X2ickzUknNGRQs77BsQYTfbBWYv2aV5qnnyATgyOgldc5516jalnkA2b2ev+Xrnqbd271jvPQNzCJL0paLGlQ0nFJf55qNMiULAyOjkm6zPt5vpKZaRs54Zw7Vvv/MUnbVE1xnwxKIrX/H0svQmRMs77BsQYh59xJ59yYc25c1TnzgtIZ/QSZGBztkLTUzK4ws6mqngj3/ZRjQkaY2YVmNiNoS/otST9VtY+8q7bauyT9QzoRIoOa9Y3vS/rt2lVrQ5Ke8spvKJkJ55utV/W4IlX7ydvMbJqZXaHqCfw/STo+pKs/7QCccxUz+6CkuyX1Sfqac25PymEhO+ZI2mZmUrW/bnXO3WVmOyTdZma/I+mIpJazoaN4zOxbktZJmm1mRyXdLOm/qXHfuFPSDaqeYHta0nsSDxipaNJP1pnZoKpl18OSfleSnHN7zOw2SXslVSR9wDk3lkLYSJFVS/IAAACQslFWAwAAyAwGRwAAAB4GRwAAAB4GRwAAAB4GRwAAAJ5MDY68qSGApugniIq+gqjoK/D1bHBkZteb2T4zO2BmUWdMp3MiCvoJoqKvICr6CkI9GRyZWZ+kL6g6F9YKSW83sxW92BYAAECcenWH7NdKOuCcOyRJZvZtSTeqesfR8/S95ELXP2uW+i65RDNtFnelxKRerOm57yc29UVh2519IcVIiq0IfaVbldkXhu3+U8+lGEm20VfKwz/+Pn32sVPOuZdNXKdXg6N5kh71fj4qafU5wVXruxslqe+SSzTwh78vSVqyabhHIQHZ0T93ftiuPHo0xUhQdKduWhO2Z2/ZnmIkQDb4x9+7HvnckYbrJBbNBM65LZK2SNJMm+WCQdHp9fUx1Iz9T0qSxvbsC5f5v5++7cEEIs2+vpXLw7a/r5C+Zu8NAyIkpZ0BEccSlEGU42+vTsg+Juky7+f5tWUAAACZ1qvB0Q5JS83sCjObKultkr7fo20BAADEpidlNedcxcw+KOluSX2Svuac2xPlsTP/+WTYPvVrl0qSLvYeOfWpSoyRFkMR09+Va64K2/337Uotjv5FCyVJlUOHO3q8PX8mvmCAHivisQToRM/OOXLO3Snpzl49PwAAQC+kdkJ2M/5f6BfX2nePjoTLrhtINh6kI81ska/TjFFcjwcAJC9T04cAAACkjcERAACAJ3NltSmD9VlGxkeqN9S+bmAwXPai+y8N2y+sO55YXAAAlFmj7+eiInMEAADgYXAEAADgyVxZrVWqzi+lHbllbdi+/OYHehZTr/UtWxy2x/YfTDGS4gr2MfsXQDP+sdiX5+NGnN8vRS+l+cgcAQAAeBgcAQAAeMw5l3YMmmmz3Gq7tqvnOPrdlZKk+TdFmqUEAEqtb+VySe1PGRI8zse0I8ire9ztu5xzqyYuJ3MEAADgydwJ2Z1qlDF69i1DYfvin4yG7crhRxKJqRP9CxdIynaMQNEU+XMXvDbp3NfXabanKFmi8dcNSpKm/HgkXNZsXyH74n7vyBwBAAB4GBwBAAB4ClNWa+TEmnr7JbflI0VKKjclQ1fW28O704ujZE5trH9IZ2/ZnlocRf7cFfm1dcMvpwXYV/kV93tH5ggAAMDD4AgAAMBTmPsctVK55qqw3X/frp5uK02dvk72DwAgqqIcS7nPEQAAQAQMjgAAADylKav57h4
added 256 node FCs, confusion matrix notebook
2021-04-10 16:56:01 +01:00
"text/plain": [
add data augmentation script
2021-04-16 23:59:20 +01:00
"<Figure size 864x720 with 1 Axes>"
added 256 node FCs, confusion matrix notebook
2021-04-10 16:56:01 +01:00
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
add data augmentation script
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"fig, ax = plt.subplots(figsize=(12, 10)\n",
added 256 node FCs, confusion matrix notebook
2021-04-10 16:56:01 +01:00
"# , dpi=400\n",
" )\n",
"\n",
add data augmentation script
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"ax.matshow(normalised_array)\n",
added 256 node FCs, confusion matrix notebook
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"\n",
add data augmentation script
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"ax.set_title('Confusion matrix')\n",
"# plt.colorbar(ax=ax)\n",
added 256 node FCs, confusion matrix notebook
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"plt.show()"
]
},
{
"cell_type": "code",
add data augmentation script
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"execution_count": 26,
"id": "831a9fab",
added 256 node FCs, confusion matrix notebook
2021-04-10 16:56:01 +01:00
"metadata": {},
"outputs": [
{
"data": {
add data augmentation script
2021-04-16 23:59:20 +01:00
"image/png": "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
added 256 node FCs, confusion matrix notebook
2021-04-10 16:56:01 +01:00
"text/plain": [
"<Figure size 864x720 with 2 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plt.figure(figsize=(12, 10)\n",
"# , dpi=400\n",
" )\n",
add data augmentation script
2021-04-16 23:59:20 +01:00
"sns.heatmap(normalised_array, xticklabels=False, yticklabels=False, cmap='inferno')\n",
added 256 node FCs, confusion matrix notebook
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"\n",
"plt.title('Confusion matrix')\n",
"plt.show()"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"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": "3.9.2"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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