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pierrelouisbescond/dcc_final_dataset_estimate.ipynb

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Data-Centric Competition - Final DataSet Estimate
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dcc_final_dataset_estimate.ipynb
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"id": "c6721c1f-7c02-45de-a66c-c3dd7cb00bb8",
"metadata": {},
"outputs": [],
"source": [
"import numpy as np"
]
},
{
"cell_type": "markdown",
"id": "aba9219a-8b6d-4911-8440-69ea59d5d883",
"metadata": {},
"source": [
"#### Let's create potential datasets sizes and errors numbers as NumPy arrays"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "34ac4b3d-8a6e-4dd5-b1b7-d844c5829e34",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[2000 2010 2020 2030 2040 2050 2060 2070 2080 2090]\n",
"[0 1 2 3 4 5 6 7 8 9]\n"
]
}
],
"source": [
"dataset_sizes = np.linspace(2000, 3000, 101, dtype=\"int\")\n",
"print(dataset_sizes[0:10])\n",
"\n",
"erroneous_labels = np.linspace(0, 1000, 1001, dtype=\"int\")\n",
"print(erroneous_labels[0:10])\n"
]
},
{
"cell_type": "markdown",
"id": "19bdc665-a859-4a4d-abcd-32a64c9336a5",
"metadata": {},
"source": [
"#### Let's iterate on each dataset size and error number to see any match with leaderboard scores"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "12df59d0-c036-4dfa-9acf-1e134398d7a9",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"********************\n",
"2180 : 318 : 0.85413\n",
"2180 : 336 : 0.84587\n",
"********************\n",
"2330 : 363 : 0.84421\n",
"********************\n",
"2420 : 345 : 0.85744\n",
"2420 : 353 : 0.85413\n",
"2420 : 364 : 0.84959\n",
"2420 : 372 : 0.84628\n",
"2420 : 373 : 0.84587\n",
"2420 : 375 : 0.84504\n",
"2420 : 377 : 0.84421\n",
"********************\n",
"2440 : 367 : 0.84959\n",
"********************\n",
"2460 : 370 : 0.84959\n",
"********************\n",
"2620 : 406 : 0.84504\n",
"********************\n",
"2820 : 437 : 0.84504\n",
"********************\n",
"2850 : 444 : 0.84421\n",
"********************\n",
"2890 : 412 : 0.85744\n",
"********************\n",
"2960 : 455 : 0.84628\n"
]
}
],
"source": [
"target_scores = [0.85744, 0.85413, 0.84959, 0.84628, 0.84587, 0.84504, 0.84421]\n",
"dataset_size_memory = 0\n",
"\n",
"for dataset_size in dataset_sizes:\n",
"\n",
" for erroneous_label in erroneous_labels:\n",
"\n",
" score = round((dataset_size-erroneous_label)/dataset_size, 5)\n",
"\n",
" if score in target_scores:\n",
"\n",
" if dataset_size_memory != dataset_size:\n",
"\n",
" print (\"*\"*20)\n",
" dataset_size_memory = dataset_size\n",
"\n",
" print(str(dataset_size).ljust(4), \":\", str(erroneous_label).ljust(3), \":\", score)\n"
]
},
{
"cell_type": "markdown",
"id": "ff3faf61-34ab-43b7-9ca8-9fdcbce520c7",
"metadata": {},
"source": [
"#### Let's infer the erroneous pictures number from the score"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "b4c5c9c1-b700-4313-9746-098874c2343b",
"metadata": {},
"outputs": [],
"source": [
"dataset_size = 2420"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "98baecf5-a0ab-4651-a8b4-4663108689cf",
"metadata": {},
"outputs": [
{
"name": "stdin",
"output_type": "stream",
"text": [
"What is your current score? 0.83430\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Your model mislabelled 401 pictures out of 2420!\n"
]
}
],
"source": [
"target_score = float(input(\"What is your current score?\"))\n",
"\n",
"erroneous_label = dataset_size\n",
"\n",
"while erroneous_label > 0:\n",
" \n",
" if target_score == round((dataset_size-erroneous_label)/dataset_size, 5):\n",
" \n",
" print(f\"Your model mislabelled {erroneous_label} pictures out of {dataset_size}!\")\n",
" break\n",
" \n",
" erroneous_label -= 1"
]
},
{
"cell_type": "markdown",
"id": "7bb97864-20ca-459a-bc7d-654f1697d1a8",
"metadata": {},
"source": [
"#### Let's display full scores table of a specific dataset size"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "9e8f6d61-a551-4407-856c-784084f08e7b",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"2420 : 0 : 1.0\n",
"2420 : 1 : 0.99959\n",
"2420 : 2 : 0.99917\n",
"2420 : 3 : 0.99876\n",
"2420 : 4 : 0.99835\n",
"2420 : 5 : 0.99793\n",
"2420 : 6 : 0.99752\n",
"2420 : 7 : 0.99711\n",
"2420 : 8 : 0.99669\n",
"2420 : 9 : 0.99628\n",
"2420 : 10 : 0.99587\n",
"2420 : 11 : 0.99545\n",
"2420 : 12 : 0.99504\n",
"2420 : 13 : 0.99463\n",
"2420 : 14 : 0.99421\n",
"2420 : 15 : 0.9938\n",
"2420 : 16 : 0.99339\n",
"2420 : 17 : 0.99298\n",
"2420 : 18 : 0.99256\n",
"2420 : 19 : 0.99215\n",
"2420 : 20 : 0.99174\n",
"2420 : 21 : 0.99132\n",
"2420 : 22 : 0.99091\n",
"2420 : 23 : 0.9905\n",
"2420 : 24 : 0.99008\n",
"2420 : 25 : 0.98967\n",
"2420 : 26 : 0.98926\n",
"2420 : 27 : 0.98884\n",
"2420 : 28 : 0.98843\n",
"2420 : 29 : 0.98802\n",
"2420 : 30 : 0.9876\n",
"2420 : 31 : 0.98719\n",
"2420 : 32 : 0.98678\n",
"2420 : 33 : 0.98636\n",
"2420 : 34 : 0.98595\n",
"2420 : 35 : 0.98554\n",
"2420 : 36 : 0.98512\n",
"2420 : 37 : 0.98471\n",
"2420 : 38 : 0.9843\n",
"2420 : 39 : 0.98388\n",
"2420 : 40 : 0.98347\n",
"2420 : 41 : 0.98306\n",
"2420 : 42 : 0.98264\n",
"2420 : 43 : 0.98223\n",
"2420 : 44 : 0.98182\n",
"2420 : 45 : 0.9814\n",
"2420 : 46 : 0.98099\n",
"2420 : 47 : 0.98058\n",
"2420 : 48 : 0.98017\n",
"2420 : 49 : 0.97975\n",
"2420 : 50 : 0.97934\n",
"2420 : 51 : 0.97893\n",
"2420 : 52 : 0.97851\n",
"2420 : 53 : 0.9781\n",
"2420 : 54 : 0.97769\n",
"2420 : 55 : 0.97727\n",
"2420 : 56 : 0.97686\n",
"2420 : 57 : 0.97645\n",
"2420 : 58 : 0.97603\n",
"2420 : 59 : 0.97562\n",
"2420 : 60 : 0.97521\n",
"2420 : 61 : 0.97479\n",
"2420 : 62 : 0.97438\n",
"2420 : 63 : 0.97397\n",
"2420 : 64 : 0.97355\n",
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"2420 : 66 : 0.97273\n",
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"2420 : 69 : 0.97149\n",
"2420 : 70 : 0.97107\n",
"2420 : 71 : 0.97066\n",
"2420 : 72 : 0.97025\n",
"2420 : 73 : 0.96983\n",
"2420 : 74 : 0.96942\n",
"2420 : 75 : 0.96901\n",
"2420 : 76 : 0.9686\n",
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"2420 : 78 : 0.96777\n",
"2420 : 79 : 0.96736\n",
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"2420 : 81 : 0.96653\n",
"2420 : 82 : 0.96612\n",
"2420 : 83 : 0.9657\n",
"2420 : 84 : 0.96529\n",
"2420 : 85 : 0.96488\n",
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"2420 : 88 : 0.96364\n",
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"2420 : 91 : 0.9624\n",
"2420 : 92 : 0.96198\n",
"2420 : 93 : 0.96157\n",
"2420 : 94 : 0.96116\n",
"2420 : 95 : 0.96074\n",
"2420 : 96 : 0.96033\n",
"2420 : 97 : 0.95992\n",
"2420 : 98 : 0.9595\n",
"2420 : 99 : 0.95909\n",
"2420 : 100 : 0.95868\n",
"2420 : 101 : 0.95826\n",
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"2420 : 103 : 0.95744\n",
"2420 : 104 : 0.95702\n",
"2420 : 105 : 0.95661\n",
"2420 : 106 : 0.9562\n",
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"2420 : 110 : 0.95455\n",
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"2420 : 116 : 0.95207\n",
"2420 : 117 : 0.95165\n",
"2420 : 118 : 0.95124\n",
"2420 : 119 : 0.95083\n",
"2420 : 120 : 0.95041\n",
"2420 : 121 : 0.95\n",
"2420 : 122 : 0.94959\n",
"2420 : 123 : 0.94917\n",
"2420 : 124 : 0.94876\n",
"2420 : 125 : 0.94835\n",
"2420 : 126 : 0.94793\n",
"2420 : 127 : 0.94752\n",
"2420 : 128 : 0.94711\n",
"2420 : 129 : 0.94669\n",
"2420 : 130 : 0.94628\n",
"2420 : 131 : 0.94587\n",
"2420 : 132 : 0.94545\n",
"2420 : 133 : 0.94504\n",
"2420 : 134 : 0.94463\n",
"2420 : 135 : 0.94421\n",
"2420 : 136 : 0.9438\n",
"2420 : 137 : 0.94339\n",
"2420 : 138 : 0.94298\n",
"2420 : 139 : 0.94256\n",
"2420 : 140 : 0.94215\n",
"2420 : 141 : 0.94174\n",
"2420 : 142 : 0.94132\n",
"2420 : 143 : 0.94091\n",
"2420 : 144 : 0.9405\n",
"2420 : 145 : 0.94008\n",
"2420 : 146 : 0.93967\n",
"2420 : 147 : 0.93926\n",
"2420 : 148 : 0.93884\n",
"2420 : 149 : 0.93843\n",
"2420 : 150 : 0.93802\n",
"2420 : 151 : 0.9376\n",
"2420 : 152 : 0.93719\n",
"2420 : 153 : 0.93678\n",
"2420 : 154 : 0.93636\n",
"2420 : 155 : 0.93595\n",
"2420 : 156 : 0.93554\n",
"2420 : 157 : 0.93512\n",
"2420 : 158 : 0.93471\n",
"2420 : 159 : 0.9343\n",
"2420 : 160 : 0.93388\n",
"2420 : 161 : 0.93347\n",
"2420 : 162 : 0.93306\n",
"2420 : 163 : 0.93264\n",
"2420 : 164 : 0.93223\n",
"2420 : 165 : 0.93182\n",
"2420 : 166 : 0.9314\n",
"2420 : 167 : 0.93099\n",
"2420 : 168 : 0.93058\n",
"2420 : 169 : 0.93017\n",
"2420 : 170 : 0.92975\n",
"2420 : 171 : 0.92934\n",
"2420 : 172 : 0.92893\n",
"2420 : 173 : 0.92851\n",
"2420 : 174 : 0.9281\n",
"2420 : 175 : 0.92769\n",
"2420 : 176 : 0.92727\n",
"2420 : 177 : 0.92686\n",
"2420 : 178 : 0.92645\n",
"2420 : 179 : 0.92603\n",
"2420 : 180 : 0.92562\n",
"2420 : 181 : 0.92521\n",
"2420 : 182 : 0.92479\n",
"2420 : 183 : 0.92438\n",
"2420 : 184 : 0.92397\n",
"2420 : 185 : 0.92355\n",
"2420 : 186 : 0.92314\n",
"2420 : 187 : 0.92273\n",
"2420 : 188 : 0.92231\n",
"2420 : 189 : 0.9219\n",
"2420 : 190 : 0.92149\n",
"2420 : 191 : 0.92107\n",
"2420 : 192 : 0.92066\n",
"2420 : 193 : 0.92025\n",
"2420 : 194 : 0.91983\n",
"2420 : 195 : 0.91942\n",
"2420 : 196 : 0.91901\n",
"2420 : 197 : 0.9186\n",
"2420 : 198 : 0.91818\n",
"2420 : 199 : 0.91777\n",
"2420 : 200 : 0.91736\n",
"2420 : 201 : 0.91694\n",
"2420 : 202 : 0.91653\n",
"2420 : 203 : 0.91612\n",
"2420 : 204 : 0.9157\n",
"2420 : 205 : 0.91529\n",
"2420 : 206 : 0.91488\n",
"2420 : 207 : 0.91446\n",
"2420 : 208 : 0.91405\n",
"2420 : 209 : 0.91364\n",
"2420 : 210 : 0.91322\n",
"2420 : 211 : 0.91281\n",
"2420 : 212 : 0.9124\n",
"2420 : 213 : 0.91198\n",
"2420 : 214 : 0.91157\n",
"2420 : 215 : 0.91116\n",
"2420 : 216 : 0.91074\n",
"2420 : 217 : 0.91033\n",
"2420 : 218 : 0.90992\n",
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"2420 : 220 : 0.90909\n",
"2420 : 221 : 0.90868\n",
"2420 : 222 : 0.90826\n",
"2420 : 223 : 0.90785\n",
"2420 : 224 : 0.90744\n",
"2420 : 225 : 0.90702\n",
"2420 : 226 : 0.90661\n",
"2420 : 227 : 0.9062\n",
"2420 : 228 : 0.90579\n",
"2420 : 229 : 0.90537\n",
"2420 : 230 : 0.90496\n",
"2420 : 231 : 0.90455\n",
"2420 : 232 : 0.90413\n",
"2420 : 233 : 0.90372\n",
"2420 : 234 : 0.90331\n",
"2420 : 235 : 0.90289\n",
"2420 : 236 : 0.90248\n",
"2420 : 237 : 0.90207\n",
"2420 : 238 : 0.90165\n",
"2420 : 239 : 0.90124\n",
"2420 : 240 : 0.90083\n",
"2420 : 241 : 0.90041\n",
"2420 : 242 : 0.9\n",
"2420 : 243 : 0.89959\n",
"2420 : 244 : 0.89917\n",
"2420 : 245 : 0.89876\n",
"2420 : 246 : 0.89835\n",
"2420 : 247 : 0.89793\n",
"2420 : 248 : 0.89752\n",
"2420 : 249 : 0.89711\n",
"2420 : 250 : 0.89669\n",
"2420 : 251 : 0.89628\n",
"2420 : 252 : 0.89587\n",
"2420 : 253 : 0.89545\n",
"2420 : 254 : 0.89504\n",
"2420 : 255 : 0.89463\n",
"2420 : 256 : 0.89421\n",
"2420 : 257 : 0.8938\n",
"2420 : 258 : 0.89339\n",
"2420 : 259 : 0.89298\n",
"2420 : 260 : 0.89256\n",
"2420 : 261 : 0.89215\n",
"2420 : 262 : 0.89174\n",
"2420 : 263 : 0.89132\n",
"2420 : 264 : 0.89091\n",
"2420 : 265 : 0.8905\n",
"2420 : 266 : 0.89008\n",
"2420 : 267 : 0.88967\n",
"2420 : 268 : 0.88926\n",
"2420 : 269 : 0.88884\n",
"2420 : 270 : 0.88843\n",
"2420 : 271 : 0.88802\n",
"2420 : 272 : 0.8876\n",
"2420 : 273 : 0.88719\n",
"2420 : 274 : 0.88678\n",
"2420 : 275 : 0.88636\n",
"2420 : 276 : 0.88595\n",
"2420 : 277 : 0.88554\n",
"2420 : 278 : 0.88512\n",
"2420 : 279 : 0.88471\n",
"2420 : 280 : 0.8843\n",
"2420 : 281 : 0.88388\n",
"2420 : 282 : 0.88347\n",
"2420 : 283 : 0.88306\n",
"2420 : 284 : 0.88264\n",
"2420 : 285 : 0.88223\n",
"2420 : 286 : 0.88182\n",
"2420 : 287 : 0.8814\n",
"2420 : 288 : 0.88099\n",
"2420 : 289 : 0.88058\n",
"2420 : 290 : 0.88017\n",
"2420 : 291 : 0.87975\n",
"2420 : 292 : 0.87934\n",
"2420 : 293 : 0.87893\n",
"2420 : 294 : 0.87851\n",
"2420 : 295 : 0.8781\n",
"2420 : 296 : 0.87769\n",
"2420 : 297 : 0.87727\n",
"2420 : 298 : 0.87686\n",
"2420 : 299 : 0.87645\n",
"2420 : 300 : 0.87603\n",
"2420 : 301 : 0.87562\n",
"2420 : 302 : 0.87521\n",
"2420 : 303 : 0.87479\n",
"2420 : 304 : 0.87438\n",
"2420 : 305 : 0.87397\n",
"2420 : 306 : 0.87355\n",
"2420 : 307 : 0.87314\n",
"2420 : 308 : 0.87273\n",
"2420 : 309 : 0.87231\n",
"2420 : 310 : 0.8719\n",
"2420 : 311 : 0.87149\n",
"2420 : 312 : 0.87107\n",
"2420 : 313 : 0.87066\n",
"2420 : 314 : 0.87025\n",
"2420 : 315 : 0.86983\n",
"2420 : 316 : 0.86942\n",
"2420 : 317 : 0.86901\n",
"2420 : 318 : 0.8686\n",
"2420 : 319 : 0.86818\n",
"2420 : 320 : 0.86777\n",
"2420 : 321 : 0.86736\n",
"2420 : 322 : 0.86694\n",
"2420 : 323 : 0.86653\n",
"2420 : 324 : 0.86612\n",
"2420 : 325 : 0.8657\n",
"2420 : 326 : 0.86529\n",
"2420 : 327 : 0.86488\n",
"2420 : 328 : 0.86446\n",
"2420 : 329 : 0.86405\n",
"2420 : 330 : 0.86364\n",
"2420 : 331 : 0.86322\n",
"2420 : 332 : 0.86281\n",
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"2420 : 335 : 0.86157\n",
"2420 : 336 : 0.86116\n",
"2420 : 337 : 0.86074\n",
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"2420 : 339 : 0.85992\n",
"2420 : 340 : 0.8595\n",
"2420 : 341 : 0.85909\n",
"2420 : 342 : 0.85868\n",
"2420 : 343 : 0.85826\n",
"2420 : 344 : 0.85785\n",
"2420 : 345 : 0.85744\n",
"2420 : 346 : 0.85702\n",
"2420 : 347 : 0.85661\n",
"2420 : 348 : 0.8562\n",
"2420 : 349 : 0.85579\n",
"2420 : 350 : 0.85537\n",
"2420 : 351 : 0.85496\n",
"2420 : 352 : 0.85455\n",
"2420 : 353 : 0.85413\n",
"2420 : 354 : 0.85372\n",
"2420 : 355 : 0.85331\n",
"2420 : 356 : 0.85289\n",
"2420 : 357 : 0.85248\n",
"2420 : 358 : 0.85207\n",
"2420 : 359 : 0.85165\n",
"2420 : 360 : 0.85124\n",
"2420 : 361 : 0.85083\n",
"2420 : 362 : 0.85041\n",
"2420 : 363 : 0.85\n",
"2420 : 364 : 0.84959\n",
"2420 : 365 : 0.84917\n",
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"2420 : 367 : 0.84835\n",
"2420 : 368 : 0.84793\n",
"2420 : 369 : 0.84752\n",
"2420 : 370 : 0.84711\n",
"2420 : 371 : 0.84669\n",
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"2420 : 373 : 0.84587\n",
"2420 : 374 : 0.84545\n",
"2420 : 375 : 0.84504\n",
"2420 : 376 : 0.84463\n",
"2420 : 377 : 0.84421\n",
"2420 : 378 : 0.8438\n",
"2420 : 379 : 0.84339\n",
"2420 : 380 : 0.84298\n",
"2420 : 381 : 0.84256\n",
"2420 : 382 : 0.84215\n",
"2420 : 383 : 0.84174\n",
"2420 : 384 : 0.84132\n",
"2420 : 385 : 0.84091\n",
"2420 : 386 : 0.8405\n",
"2420 : 387 : 0.84008\n",
"2420 : 388 : 0.83967\n",
"2420 : 389 : 0.83926\n",
"2420 : 390 : 0.83884\n",
"2420 : 391 : 0.83843\n",
"2420 : 392 : 0.83802\n",
"2420 : 393 : 0.8376\n",
"2420 : 394 : 0.83719\n",
"2420 : 395 : 0.83678\n",
"2420 : 396 : 0.83636\n",
"2420 : 397 : 0.83595\n",
"2420 : 398 : 0.83554\n",
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"2420 : 919 : 0.62025\n",
"2420 : 920 : 0.61983\n",
"2420 : 921 : 0.61942\n",
"2420 : 922 : 0.61901\n",
"2420 : 923 : 0.6186\n",
"2420 : 924 : 0.61818\n",
"2420 : 925 : 0.61777\n",
"2420 : 926 : 0.61736\n",
"2420 : 927 : 0.61694\n",
"2420 : 928 : 0.61653\n",
"2420 : 929 : 0.61612\n",
"2420 : 930 : 0.6157\n",
"2420 : 931 : 0.61529\n",
"2420 : 932 : 0.61488\n",
"2420 : 933 : 0.61446\n",
"2420 : 934 : 0.61405\n",
"2420 : 935 : 0.61364\n",
"2420 : 936 : 0.61322\n",
"2420 : 937 : 0.61281\n",
"2420 : 938 : 0.6124\n",
"2420 : 939 : 0.61198\n",
"2420 : 940 : 0.61157\n",
"2420 : 941 : 0.61116\n",
"2420 : 942 : 0.61074\n",
"2420 : 943 : 0.61033\n",
"2420 : 944 : 0.60992\n",
"2420 : 945 : 0.6095\n",
"2420 : 946 : 0.60909\n",
"2420 : 947 : 0.60868\n",
"2420 : 948 : 0.60826\n",
"2420 : 949 : 0.60785\n",
"2420 : 950 : 0.60744\n",
"2420 : 951 : 0.60702\n",
"2420 : 952 : 0.60661\n",
"2420 : 953 : 0.6062\n",
"2420 : 954 : 0.60579\n",
"2420 : 955 : 0.60537\n",
"2420 : 956 : 0.60496\n",
"2420 : 957 : 0.60455\n",
"2420 : 958 : 0.60413\n",
"2420 : 959 : 0.60372\n",
"2420 : 960 : 0.60331\n",
"2420 : 961 : 0.60289\n",
"2420 : 962 : 0.60248\n",
"2420 : 963 : 0.60207\n",
"2420 : 964 : 0.60165\n",
"2420 : 965 : 0.60124\n",
"2420 : 966 : 0.60083\n",
"2420 : 967 : 0.60041\n",
"2420 : 968 : 0.6\n",
"2420 : 969 : 0.59959\n",
"2420 : 970 : 0.59917\n",
"2420 : 971 : 0.59876\n",
"2420 : 972 : 0.59835\n",
"2420 : 973 : 0.59793\n",
"2420 : 974 : 0.59752\n",
"2420 : 975 : 0.59711\n",
"2420 : 976 : 0.59669\n",
"2420 : 977 : 0.59628\n",
"2420 : 978 : 0.59587\n",
"2420 : 979 : 0.59545\n",
"2420 : 980 : 0.59504\n",
"2420 : 981 : 0.59463\n",
"2420 : 982 : 0.59421\n",
"2420 : 983 : 0.5938\n",
"2420 : 984 : 0.59339\n",
"2420 : 985 : 0.59298\n",
"2420 : 986 : 0.59256\n",
"2420 : 987 : 0.59215\n",
"2420 : 988 : 0.59174\n",
"2420 : 989 : 0.59132\n",
"2420 : 990 : 0.59091\n",
"2420 : 991 : 0.5905\n",
"2420 : 992 : 0.59008\n",
"2420 : 993 : 0.58967\n",
"2420 : 994 : 0.58926\n",
"2420 : 995 : 0.58884\n",
"2420 : 996 : 0.58843\n",
"2420 : 997 : 0.58802\n",
"2420 : 998 : 0.5876\n",
"2420 : 999 : 0.58719\n",
"2420 : 1000 : 0.58678\n"
]
}
],
"source": [
"dataset_size = 2420\n",
"\n",
"for erroneous_label in erroneous_labels:\n",
"\n",
" score = round((dataset_size-erroneous_label)/dataset_size, 5)\n",
"\n",
" print(str(dataset_size).ljust(4), \":\", str(erroneous_label).ljust(3), \":\", score)\n"
]
}
],
"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": "3.9.5"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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