title: How are decision trees in random forest algorithms made?
body: <p>I was suddenly presented with the profound question of how does a computer generate a decision tree.</p>
  <p>For example, consider the problem of predicting a specific flower species using the random forest algorithm. There are two specific attributes of a flower (petal width, petal length) that distinguish the species.</p>
  <p>In terms of the flower problem, when using sclearn's Python decisiontreemaker(), how does the computer figure out what petal width and petal length to create the tree? Also, does a random forest algorithm create these decision trees by brute forcing and testing every single variation of a tree by weighing entrophy?</p>