Decision tree – Your secret weapon
What a decision tree is
The decision tree is a tree-shaped diagram that shows a statistical probability or determines a course of action. It shows the steps how and why one choice may lead to another. Therefore, it is a suitable decision-making tool for research analysis or planning strategy to find the best way to reach a goal.
It has three main parts: a root node, leaf nodes and branches. The root node is the target value that we are seeking how it could be reached. The leaf nodes contain the information about criteria. The branches are connecting the nodes and show the route through the leaves to the target value.
Making the tree
For the first sight it looks so difficult to create a decision tree from data. The good news is AnswerMiner builds the tree automatically from the dataset. There are only a few steps to make a decision tree.
- Select the target value or starting point that will be the root node.
- Highlight the columns that you would like to involve.
- The branches are created automatically and show the strength of the connections between the nodes.
Watch the short video below and see how it works
Tree in action
More and more sectors are using because it’s a powerful visualization tool. It’s most commonly used in the financial sector by loan approval or portfolio management etc… In our data-driven world other sectors also discover its usefulness and apply it to optimize their strategy to reach the goal and avoid the pitfalls.
Obviously, the decision tree is a hidden weapon to make a prediction using your data. The main question is that how much time do you need to analyse and understand your data? AnswerMiner makes the exploration of data much faster and easier and also makes decision tree in a second.