# Difference Between Decision Table and Decision Tree

## Decision Table & Decision Tree

• Decision tables and decision trees are two popular methods used in decision-making and problem-solving.
• The key Difference Between Decision Table and Decision Tree is that Decision Table is just a tabular representation whereas Decision Tree is a graph representation.

### Comparison Chart

• Decision Table and Decision Tree both have different features and functionalities, here is a comparison of some key features between them.
Decision Table Decision Tree
Structure Tabular Graphical
Representation Lists out possible conditions Maps out possible outcomes
Format Grid or matrix Tree-like structure
Rows Different combinations of conditions Sequential decisions or conditions
Columns Corresponding actions Branches of possible outcomes
Complexity Useful for complex scenarios Useful for simple to moderate scenarios
Interdependence Can account for overlapping or interdependent effects Not as well-suited for interdependent factors
Decision-Making Deals with all possible conditions and actions in one place Requires following through branches to determine outcomes
Implementation Can be implemented manually or through software Typically implemented through software
Analysis Suitable for rule-based analysis Suitable for probability-based analysis

### Decision Table

• There are two types of decision tables:
1. Extendedentry table
2. Limitedentry table

#### Decision Table Advantages:

• Advantages:The table shows cause and effect relationships.
• Tables are of standardized format.
• Semi – standardized languages can be employed in these tables.
• Complex tables can easily be split into simpler tables.
• Table user’s are not required to possess computer knowledge.

#### Decision Table Disadvantages:

• Decision tables do not scale up well. We need to “factor” large tables into smaller ones to remove redundancy
• Total sequence – The total sequence is not clearly shown, i.e., no overall picture is given by decision tables as presented by flowcharts.
• Logic – Where the logic of a system is simple, flowcharts nearly always serve the purpose better than a decision table.

### Decision Tree

• There are two types of decision tree.
1. Categorical variable decision tree
2. Continuous variable decision tree

#### Decision Tree Advantages:

• A decision tree is easy to understand and interpret.
• Expert opinion and preferences can be included, as well as hard data.
• Can be used with other decision techniques.
• New scenarios can easily be added.

#### Decision Tree Disadvantages:

• They are unstable, meaning that a small change in the data can lead to a large change in the structure of the optimal decision tree.
• They are often relatively inaccurate. Many other predictors perform better with similar data. This can be remedied by replacing a single decision tree with a random forest of decision trees, but a random forest is not as easy to interpret as a single decision tree.
• Calculations can get very complex, particularly if many values are uncertain and/or if many outcomes are linked