Prerequisite: Decision Tree in Machine Learning

The steps used for making Decision Tree are -

  1. Get the list of rows (dataset) which are taken into consideration for making a decision tree (recursively at each node).
  2. Calculate uncertainty of our dataset or Gini impurity or how much our dataset is mixed up, etc.
  3. Generate list of all questions which need to be asked at that node.
  4. Partition rows into True rows and False rows based on each question asked.
  5. Calculate information gain based on Gini Impurity and partition of data from the previous step.
  6. Update the highest information gain based on each question asked.
  7. Update question based on information gain (higher information gain).
  8. Divide the node on the question. Repeat again from step 1 until we get pure node (leaf nodes).