Modelo de previsão de receitas para filmes
Samuel
12 de julho de 2019
Nosso intuito é construir um modelo de predição de receitas de lançamentos cinematográficos, através das seguintes variáveis disponíveis:
- pop, a popularidade do filme medida pelo índice do IMDB;
- budget o orçamento do filme em dólares;
- runtime a duração do filme em minutos;
- language variável dummy sobre o idioma do filme, em que vale \(1\) se ele é falado em inglês e \(0\) caso contrário.
- revenue a receita do filme em dólares, como nossa variável resposta.
Importando os dados de treino e tratanto nossa base de dados
train <- read.csv("~/trabalhos estcomp/train.csv")
library(randomForest)
library(tidyverse)
dados <- na.omit(train)
dados <- dados[dados$budget > 100000,]
pop <- dados$popularity
revenue <- dados$revenue
budget <- dados$budget
runtime <- dados$runtime
language <- as.integer(dados$original_language == 'en')
base <- as.data.frame(cbind(pop, revenue, budget, runtime, language))Usando agora o metodo de Random Forest para criarmos um modelo preditivo com base na regressão, temos com 200 árvores:
rf = randomForest(revenue~. , data = base , importance = TRUE, ntrees = 200, do.trace = T)## | Out-of-bag |
## Tree | MSE %Var(y) |
## 1 | 1.42e+16 58.00 |
## 2 | 2.046e+16 83.54 |
## 3 | 1.982e+16 80.92 |
## 4 | 1.822e+16 74.40 |
## 5 | 1.629e+16 66.53 |
## 6 | 1.505e+16 61.45 |
## 7 | 1.44e+16 58.80 |
## 8 | 1.409e+16 57.54 |
## 9 | 1.329e+16 54.27 |
## 10 | 1.294e+16 52.85 |
## 11 | 1.323e+16 54.03 |
## 12 | 1.291e+16 52.69 |
## 13 | 1.257e+16 51.32 |
## 14 | 1.24e+16 50.63 |
## 15 | 1.217e+16 49.71 |
## 16 | 1.197e+16 48.86 |
## 17 | 1.177e+16 48.08 |
## 18 | 1.154e+16 47.11 |
## 19 | 1.131e+16 46.18 |
## 20 | 1.164e+16 47.51 |
## 21 | 1.136e+16 46.40 |
## 22 | 1.12e+16 45.72 |
## 23 | 1.109e+16 45.28 |
## 24 | 1.094e+16 44.68 |
## 25 | 1.087e+16 44.40 |
## 26 | 1.079e+16 44.08 |
## 27 | 1.073e+16 43.81 |
## 28 | 1.065e+16 43.50 |
## 29 | 1.067e+16 43.57 |
## 30 | 1.066e+16 43.55 |
## 31 | 1.064e+16 43.46 |
## 32 | 1.075e+16 43.90 |
## 33 | 1.061e+16 43.31 |
## 34 | 1.06e+16 43.28 |
## 35 | 1.08e+16 44.09 |
## 36 | 1.089e+16 44.48 |
## 37 | 1.085e+16 44.30 |
## 38 | 1.09e+16 44.50 |
## 39 | 1.083e+16 44.23 |
## 40 | 1.077e+16 43.98 |
## 41 | 1.082e+16 44.17 |
## 42 | 1.087e+16 44.37 |
## 43 | 1.085e+16 44.30 |
## 44 | 1.081e+16 44.15 |
## 45 | 1.098e+16 44.83 |
## 46 | 1.099e+16 44.88 |
## 47 | 1.093e+16 44.64 |
## 48 | 1.099e+16 44.86 |
## 49 | 1.094e+16 44.66 |
## 50 | 1.104e+16 45.08 |
## 51 | 1.098e+16 44.81 |
## 52 | 1.09e+16 44.49 |
## 53 | 1.084e+16 44.25 |
## 54 | 1.078e+16 44.01 |
## 55 | 1.074e+16 43.84 |
## 56 | 1.069e+16 43.64 |
## 57 | 1.068e+16 43.60 |
## 58 | 1.062e+16 43.37 |
## 59 | 1.056e+16 43.13 |
## 60 | 1.055e+16 43.09 |
## 61 | 1.053e+16 42.99 |
## 62 | 1.052e+16 42.94 |
## 63 | 1.05e+16 42.89 |
## 64 | 1.055e+16 43.10 |
## 65 | 1.052e+16 42.94 |
## 66 | 1.049e+16 42.82 |
## 67 | 1.056e+16 43.10 |
## 68 | 1.055e+16 43.07 |
## 69 | 1.056e+16 43.11 |
## 70 | 1.058e+16 43.18 |
## 71 | 1.056e+16 43.12 |
## 72 | 1.055e+16 43.08 |
## 73 | 1.053e+16 42.99 |
## 74 | 1.052e+16 42.97 |
## 75 | 1.048e+16 42.79 |
## 76 | 1.046e+16 42.70 |
## 77 | 1.043e+16 42.58 |
## 78 | 1.039e+16 42.42 |
## 79 | 1.038e+16 42.37 |
## 80 | 1.034e+16 42.21 |
## 81 | 1.036e+16 42.31 |
## 82 | 1.037e+16 42.33 |
## 83 | 1.037e+16 42.34 |
## 84 | 1.034e+16 42.23 |
## 85 | 1.031e+16 42.10 |
## 86 | 1.032e+16 42.15 |
## 87 | 1.031e+16 42.11 |
## 88 | 1.029e+16 42.01 |
## 89 | 1.026e+16 41.90 |
## 90 | 1.026e+16 41.90 |
## 91 | 1.029e+16 42.01 |
## 92 | 1.029e+16 42.03 |
## 93 | 1.028e+16 41.99 |
## 94 | 1.034e+16 42.21 |
## 95 | 1.033e+16 42.19 |
## 96 | 1.033e+16 42.20 |
## 97 | 1.036e+16 42.30 |
## 98 | 1.037e+16 42.34 |
## 99 | 1.036e+16 42.29 |
## 100 | 1.034e+16 42.22 |
## 101 | 1.039e+16 42.44 |
## 102 | 1.036e+16 42.31 |
## 103 | 1.034e+16 42.23 |
## 104 | 1.037e+16 42.34 |
## 105 | 1.033e+16 42.20 |
## 106 | 1.031e+16 42.08 |
## 107 | 1.03e+16 42.05 |
## 108 | 1.029e+16 42.00 |
## 109 | 1.032e+16 42.15 |
## 110 | 1.03e+16 42.06 |
## 111 | 1.03e+16 42.05 |
## 112 | 1.034e+16 42.22 |
## 113 | 1.037e+16 42.32 |
## 114 | 1.043e+16 42.59 |
## 115 | 1.041e+16 42.52 |
## 116 | 1.041e+16 42.50 |
## 117 | 1.039e+16 42.42 |
## 118 | 1.038e+16 42.37 |
## 119 | 1.038e+16 42.38 |
## 120 | 1.039e+16 42.44 |
## 121 | 1.041e+16 42.50 |
## 122 | 1.041e+16 42.51 |
## 123 | 1.041e+16 42.51 |
## 124 | 1.04e+16 42.45 |
## 125 | 1.039e+16 42.43 |
## 126 | 1.04e+16 42.45 |
## 127 | 1.038e+16 42.37 |
## 128 | 1.04e+16 42.46 |
## 129 | 1.039e+16 42.44 |
## 130 | 1.046e+16 42.71 |
## 131 | 1.047e+16 42.75 |
## 132 | 1.046e+16 42.72 |
## 133 | 1.047e+16 42.73 |
## 134 | 1.044e+16 42.62 |
## 135 | 1.041e+16 42.49 |
## 136 | 1.038e+16 42.40 |
## 137 | 1.037e+16 42.34 |
## 138 | 1.036e+16 42.31 |
## 139 | 1.035e+16 42.28 |
## 140 | 1.035e+16 42.27 |
## 141 | 1.035e+16 42.25 |
## 142 | 1.033e+16 42.18 |
## 143 | 1.032e+16 42.12 |
## 144 | 1.029e+16 42.01 |
## 145 | 1.029e+16 42.01 |
## 146 | 1.027e+16 41.94 |
## 147 | 1.026e+16 41.88 |
## 148 | 1.026e+16 41.91 |
## 149 | 1.025e+16 41.87 |
## 150 | 1.029e+16 42.01 |
## 151 | 1.028e+16 41.96 |
## 152 | 1.027e+16 41.95 |
## 153 | 1.025e+16 41.85 |
## 154 | 1.024e+16 41.80 |
## 155 | 1.026e+16 41.88 |
## 156 | 1.026e+16 41.89 |
## 157 | 1.027e+16 41.93 |
## 158 | 1.026e+16 41.90 |
## 159 | 1.026e+16 41.89 |
## 160 | 1.025e+16 41.84 |
## 161 | 1.024e+16 41.80 |
## 162 | 1.024e+16 41.83 |
## 163 | 1.023e+16 41.77 |
## 164 | 1.021e+16 41.68 |
## 165 | 1.02e+16 41.65 |
## 166 | 1.02e+16 41.65 |
## 167 | 1.02e+16 41.64 |
## 168 | 1.02e+16 41.66 |
## 169 | 1.02e+16 41.63 |
## 170 | 1.019e+16 41.60 |
## 171 | 1.018e+16 41.55 |
## 172 | 1.016e+16 41.50 |
## 173 | 1.015e+16 41.46 |
## 174 | 1.019e+16 41.60 |
## 175 | 1.02e+16 41.64 |
## 176 | 1.02e+16 41.63 |
## 177 | 1.02e+16 41.66 |
## 178 | 1.023e+16 41.78 |
## 179 | 1.024e+16 41.81 |
## 180 | 1.026e+16 41.90 |
## 181 | 1.027e+16 41.93 |
## 182 | 1.026e+16 41.89 |
## 183 | 1.026e+16 41.89 |
## 184 | 1.025e+16 41.85 |
## 185 | 1.026e+16 41.90 |
## 186 | 1.025e+16 41.84 |
## 187 | 1.024e+16 41.80 |
## 188 | 1.022e+16 41.73 |
## 189 | 1.021e+16 41.70 |
## 190 | 1.022e+16 41.71 |
## 191 | 1.023e+16 41.78 |
## 192 | 1.025e+16 41.86 |
## 193 | 1.025e+16 41.86 |
## 194 | 1.025e+16 41.84 |
## 195 | 1.027e+16 41.95 |
## 196 | 1.027e+16 41.95 |
## 197 | 1.028e+16 41.96 |
## 198 | 1.028e+16 41.97 |
## 199 | 1.028e+16 41.97 |
## 200 | 1.027e+16 41.92 |
## 201 | 1.027e+16 41.91 |
## 202 | 1.028e+16 41.99 |
## 203 | 1.029e+16 42.01 |
## 204 | 1.03e+16 42.04 |
## 205 | 1.03e+16 42.07 |
## 206 | 1.03e+16 42.05 |
## 207 | 1.029e+16 42.03 |
## 208 | 1.03e+16 42.05 |
## 209 | 1.029e+16 42.01 |
## 210 | 1.028e+16 41.96 |
## 211 | 1.028e+16 41.96 |
## 212 | 1.028e+16 41.97 |
## 213 | 1.027e+16 41.92 |
## 214 | 1.026e+16 41.88 |
## 215 | 1.027e+16 41.93 |
## 216 | 1.027e+16 41.95 |
## 217 | 1.027e+16 41.94 |
## 218 | 1.027e+16 41.94 |
## 219 | 1.029e+16 42.03 |
## 220 | 1.029e+16 42.02 |
## 221 | 1.028e+16 41.99 |
## 222 | 1.028e+16 41.99 |
## 223 | 1.03e+16 42.08 |
## 224 | 1.03e+16 42.05 |
## 225 | 1.029e+16 42.03 |
## 226 | 1.03e+16 42.06 |
## 227 | 1.03e+16 42.04 |
## 228 | 1.029e+16 42.01 |
## 229 | 1.028e+16 41.99 |
## 230 | 1.03e+16 42.04 |
## 231 | 1.03e+16 42.06 |
## 232 | 1.03e+16 42.06 |
## 233 | 1.03e+16 42.04 |
## 234 | 1.03e+16 42.05 |
## 235 | 1.028e+16 41.99 |
## 236 | 1.029e+16 42.00 |
## 237 | 1.028e+16 41.98 |
## 238 | 1.029e+16 42.02 |
## 239 | 1.028e+16 41.97 |
## 240 | 1.028e+16 41.97 |
## 241 | 1.027e+16 41.94 |
## 242 | 1.028e+16 41.96 |
## 243 | 1.031e+16 42.09 |
## 244 | 1.031e+16 42.08 |
## 245 | 1.03e+16 42.07 |
## 246 | 1.031e+16 42.09 |
## 247 | 1.03e+16 42.07 |
## 248 | 1.031e+16 42.08 |
## 249 | 1.031e+16 42.09 |
## 250 | 1.031e+16 42.09 |
## 251 | 1.03e+16 42.07 |
## 252 | 1.03e+16 42.06 |
## 253 | 1.03e+16 42.04 |
## 254 | 1.029e+16 42.03 |
## 255 | 1.03e+16 42.05 |
## 256 | 1.029e+16 42.00 |
## 257 | 1.028e+16 41.97 |
## 258 | 1.028e+16 41.97 |
## 259 | 1.028e+16 41.96 |
## 260 | 1.028e+16 41.98 |
## 261 | 1.028e+16 41.98 |
## 262 | 1.029e+16 42.00 |
## 263 | 1.028e+16 41.98 |
## 264 | 1.028e+16 41.96 |
## 265 | 1.027e+16 41.92 |
## 266 | 1.027e+16 41.93 |
## 267 | 1.027e+16 41.92 |
## 268 | 1.027e+16 41.93 |
## 269 | 1.027e+16 41.95 |
## 270 | 1.027e+16 41.94 |
## 271 | 1.027e+16 41.93 |
## 272 | 1.027e+16 41.91 |
## 273 | 1.025e+16 41.87 |
## 274 | 1.024e+16 41.82 |
## 275 | 1.023e+16 41.79 |
## 276 | 1.023e+16 41.78 |
## 277 | 1.024e+16 41.83 |
## 278 | 1.024e+16 41.81 |
## 279 | 1.025e+16 41.84 |
## 280 | 1.024e+16 41.82 |
## 281 | 1.024e+16 41.81 |
## 282 | 1.024e+16 41.80 |
## 283 | 1.024e+16 41.81 |
## 284 | 1.024e+16 41.80 |
## 285 | 1.024e+16 41.80 |
## 286 | 1.023e+16 41.78 |
## 287 | 1.024e+16 41.80 |
## 288 | 1.026e+16 41.89 |
## 289 | 1.026e+16 41.88 |
## 290 | 1.026e+16 41.88 |
## 291 | 1.025e+16 41.86 |
## 292 | 1.024e+16 41.83 |
## 293 | 1.025e+16 41.87 |
## 294 | 1.025e+16 41.86 |
## 295 | 1.025e+16 41.84 |
## 296 | 1.025e+16 41.84 |
## 297 | 1.024e+16 41.83 |
## 298 | 1.025e+16 41.84 |
## 299 | 1.027e+16 41.93 |
## 300 | 1.027e+16 41.94 |
## 301 | 1.027e+16 41.95 |
## 302 | 1.027e+16 41.93 |
## 303 | 1.026e+16 41.88 |
## 304 | 1.026e+16 41.88 |
## 305 | 1.026e+16 41.88 |
## 306 | 1.027e+16 41.94 |
## 307 | 1.027e+16 41.93 |
## 308 | 1.027e+16 41.92 |
## 309 | 1.026e+16 41.90 |
## 310 | 1.027e+16 41.94 |
## 311 | 1.026e+16 41.89 |
## 312 | 1.025e+16 41.85 |
## 313 | 1.024e+16 41.82 |
## 314 | 1.025e+16 41.84 |
## 315 | 1.024e+16 41.83 |
## 316 | 1.024e+16 41.80 |
## 317 | 1.023e+16 41.78 |
## 318 | 1.022e+16 41.75 |
## 319 | 1.022e+16 41.74 |
## 320 | 1.022e+16 41.74 |
## 321 | 1.023e+16 41.76 |
## 322 | 1.022e+16 41.74 |
## 323 | 1.022e+16 41.74 |
## 324 | 1.023e+16 41.75 |
## 325 | 1.023e+16 41.78 |
## 326 | 1.024e+16 41.80 |
## 327 | 1.024e+16 41.81 |
## 328 | 1.024e+16 41.81 |
## 329 | 1.024e+16 41.81 |
## 330 | 1.024e+16 41.83 |
## 331 | 1.024e+16 41.80 |
## 332 | 1.024e+16 41.81 |
## 333 | 1.023e+16 41.76 |
## 334 | 1.022e+16 41.72 |
## 335 | 1.022e+16 41.74 |
## 336 | 1.022e+16 41.71 |
## 337 | 1.022e+16 41.72 |
## 338 | 1.022e+16 41.72 |
## 339 | 1.023e+16 41.77 |
## 340 | 1.023e+16 41.76 |
## 341 | 1.025e+16 41.84 |
## 342 | 1.024e+16 41.81 |
## 343 | 1.023e+16 41.77 |
## 344 | 1.023e+16 41.76 |
## 345 | 1.023e+16 41.78 |
## 346 | 1.024e+16 41.80 |
## 347 | 1.024e+16 41.80 |
## 348 | 1.023e+16 41.78 |
## 349 | 1.023e+16 41.76 |
## 350 | 1.023e+16 41.77 |
## 351 | 1.024e+16 41.80 |
## 352 | 1.025e+16 41.85 |
## 353 | 1.025e+16 41.84 |
## 354 | 1.025e+16 41.85 |
## 355 | 1.025e+16 41.84 |
## 356 | 1.025e+16 41.85 |
## 357 | 1.025e+16 41.85 |
## 358 | 1.025e+16 41.85 |
## 359 | 1.025e+16 41.86 |
## 360 | 1.025e+16 41.85 |
## 361 | 1.025e+16 41.84 |
## 362 | 1.027e+16 41.93 |
## 363 | 1.027e+16 41.95 |
## 364 | 1.027e+16 41.94 |
## 365 | 1.027e+16 41.93 |
## 366 | 1.026e+16 41.89 |
## 367 | 1.025e+16 41.86 |
## 368 | 1.026e+16 41.88 |
## 369 | 1.025e+16 41.87 |
## 370 | 1.025e+16 41.86 |
## 371 | 1.025e+16 41.84 |
## 372 | 1.027e+16 41.93 |
## 373 | 1.026e+16 41.91 |
## 374 | 1.026e+16 41.91 |
## 375 | 1.026e+16 41.89 |
## 376 | 1.026e+16 41.91 |
## 377 | 1.028e+16 41.96 |
## 378 | 1.027e+16 41.93 |
## 379 | 1.026e+16 41.89 |
## 380 | 1.026e+16 41.89 |
## 381 | 1.025e+16 41.87 |
## 382 | 1.025e+16 41.86 |
## 383 | 1.024e+16 41.83 |
## 384 | 1.026e+16 41.89 |
## 385 | 1.026e+16 41.87 |
## 386 | 1.026e+16 41.88 |
## 387 | 1.026e+16 41.88 |
## 388 | 1.026e+16 41.87 |
## 389 | 1.025e+16 41.85 |
## 390 | 1.024e+16 41.82 |
## 391 | 1.024e+16 41.83 |
## 392 | 1.025e+16 41.86 |
## 393 | 1.027e+16 41.93 |
## 394 | 1.027e+16 41.92 |
## 395 | 1.027e+16 41.93 |
## 396 | 1.027e+16 41.93 |
## 397 | 1.028e+16 41.95 |
## 398 | 1.028e+16 41.99 |
## 399 | 1.028e+16 41.97 |
## 400 | 1.028e+16 41.97 |
## 401 | 1.029e+16 42.03 |
## 402 | 1.03e+16 42.07 |
## 403 | 1.03e+16 42.07 |
## 404 | 1.03e+16 42.05 |
## 405 | 1.03e+16 42.07 |
## 406 | 1.03e+16 42.06 |
## 407 | 1.03e+16 42.06 |
## 408 | 1.03e+16 42.06 |
## 409 | 1.03e+16 42.06 |
## 410 | 1.03e+16 42.04 |
## 411 | 1.03e+16 42.04 |
## 412 | 1.029e+16 42.04 |
## 413 | 1.029e+16 42.02 |
## 414 | 1.028e+16 41.98 |
## 415 | 1.027e+16 41.94 |
## 416 | 1.027e+16 41.92 |
## 417 | 1.026e+16 41.89 |
## 418 | 1.026e+16 41.87 |
## 419 | 1.024e+16 41.83 |
## 420 | 1.024e+16 41.80 |
## 421 | 1.023e+16 41.79 |
## 422 | 1.024e+16 41.83 |
## 423 | 1.024e+16 41.82 |
## 424 | 1.024e+16 41.82 |
## 425 | 1.024e+16 41.79 |
## 426 | 1.023e+16 41.78 |
## 427 | 1.023e+16 41.76 |
## 428 | 1.022e+16 41.74 |
## 429 | 1.024e+16 41.80 |
## 430 | 1.023e+16 41.79 |
## 431 | 1.025e+16 41.86 |
## 432 | 1.025e+16 41.85 |
## 433 | 1.025e+16 41.86 |
## 434 | 1.025e+16 41.85 |
## 435 | 1.025e+16 41.85 |
## 436 | 1.024e+16 41.83 |
## 437 | 1.024e+16 41.81 |
## 438 | 1.024e+16 41.79 |
## 439 | 1.023e+16 41.76 |
## 440 | 1.023e+16 41.75 |
## 441 | 1.022e+16 41.72 |
## 442 | 1.022e+16 41.72 |
## 443 | 1.022e+16 41.73 |
## 444 | 1.022e+16 41.74 |
## 445 | 1.022e+16 41.72 |
## 446 | 1.022e+16 41.74 |
## 447 | 1.022e+16 41.73 |
## 448 | 1.022e+16 41.71 |
## 449 | 1.021e+16 41.70 |
## 450 | 1.021e+16 41.68 |
## 451 | 1.02e+16 41.66 |
## 452 | 1.02e+16 41.65 |
## 453 | 1.02e+16 41.66 |
## 454 | 1.02e+16 41.66 |
## 455 | 1.019e+16 41.62 |
## 456 | 1.021e+16 41.68 |
## 457 | 1.021e+16 41.68 |
## 458 | 1.02e+16 41.67 |
## 459 | 1.02e+16 41.67 |
## 460 | 1.021e+16 41.70 |
## 461 | 1.021e+16 41.69 |
## 462 | 1.02e+16 41.67 |
## 463 | 1.02e+16 41.65 |
## 464 | 1.02e+16 41.63 |
## 465 | 1.019e+16 41.59 |
## 466 | 1.018e+16 41.59 |
## 467 | 1.02e+16 41.63 |
## 468 | 1.02e+16 41.63 |
## 469 | 1.019e+16 41.62 |
## 470 | 1.02e+16 41.66 |
## 471 | 1.02e+16 41.63 |
## 472 | 1.019e+16 41.62 |
## 473 | 1.019e+16 41.61 |
## 474 | 1.019e+16 41.60 |
## 475 | 1.018e+16 41.58 |
## 476 | 1.019e+16 41.59 |
## 477 | 1.019e+16 41.63 |
## 478 | 1.019e+16 41.63 |
## 479 | 1.019e+16 41.61 |
## 480 | 1.019e+16 41.61 |
## 481 | 1.019e+16 41.62 |
## 482 | 1.019e+16 41.62 |
## 483 | 1.019e+16 41.62 |
## 484 | 1.019e+16 41.61 |
## 485 | 1.02e+16 41.63 |
## 486 | 1.019e+16 41.62 |
## 487 | 1.019e+16 41.62 |
## 488 | 1.019e+16 41.60 |
## 489 | 1.019e+16 41.59 |
## 490 | 1.018e+16 41.57 |
## 491 | 1.018e+16 41.57 |
## 492 | 1.017e+16 41.54 |
## 493 | 1.018e+16 41.58 |
## 494 | 1.018e+16 41.56 |
## 495 | 1.017e+16 41.54 |
## 496 | 1.017e+16 41.54 |
## 497 | 1.017e+16 41.52 |
## 498 | 1.018e+16 41.58 |
## 499 | 1.018e+16 41.56 |
## 500 | 1.019e+16 41.59 |rf##
## Call:
## randomForest(formula = revenue ~ ., data = base, importance = TRUE, ntrees = 200, do.trace = T)
## Type of random forest: regression
## Number of trees: 500
## No. of variables tried at each split: 1
##
## Mean of squared residuals: 1.018539e+16
## % Var explained: 58.41plot(rf, main = 'Erro Regressão Random Forest')
Ou seja, há uma estabilização do erro por volta de \(200\) árvores e a variabilidade da variável resposta é explicada por cerca de \(56,7\%\) da variação das variáveis explicativas.
Além disso:
## %IncMSE IncNodePurity
## pop 4.962122e+15 1.028268e+19
## budget 1.215862e+16 1.659283e+19
## runtime 1.093565e+15 3.581220e+18
## language 6.991284e+14 7.235766e+17Desempenham maior importância na receita do filme, por ordem, o orçamento, a popularida, o tempo de execução e o idioma. O que nos dá o insight de que grandes orçamentos e boas campanhas de marketing e divulgação são realmente essenciais para o bom retorno financeiro de um filme.