A decision making tree is essentially a diagram that represents, in a specially organized way, the decisions, the main external or other events that introduce uncertainty, as well as possible outcomes of all those decisions and events.
D. Ghosh Roy
The minimum depth of a leaf in a decision tree is typically 0, meaning that a leaf node can be at the same level as its parent node.
Decision trees are a popular tool in machine learning for making decisions based on input data. Here are some examples to help you understand how they work: Example: Predicting whether a customer will buy a product based on their age and income. Solution: The decision tree would split the data based on age and income, creating branches that lead to a final decision of whether the customer is likely to buy the product or not. Example: Classifying emails as spam or not spam based on keywords. Solution: The decision tree would analyze the presence of specific keywords in the email to determine if it is spam or not. Example: Predicting the likelihood of a student passing an exam based on study hours and previous grades. Solution: The decision tree would use study hours and previous grades as criteria to predict whether a student is likely to pass the exam. These examples demonstrate how decision trees can be used to make predictions or classifications based on input data.
The optimal decision tree depth for maximizing accuracy in a classification model depends on the specific dataset and problem. It is typically determined through techniques like cross-validation or grid search. In general, a deeper tree may capture more complex patterns but can lead to overfitting, while a shallower tree may be simpler but could underfit the data. It is important to find a balance that maximizes accuracy without overfitting.
No, you can use a decision structure to test a condition in any part of the program and execute some action based on the outcome but you cannot use a decision structure alone to write a complete program.
A game tree is a visual representation of the possible outcomes and decisions in a game. It shows all the possible moves that players can make at each decision point, branching out into different paths based on those choices. This helps players analyze and strategize their moves by considering the potential consequences of each decision.
what is a decision tree???
A decision tree will help a manager decide which direction that he will moe the business in. e.g. if a business is looking to expand than they would be able to use a decision tree in order to come to a decision in terms of which direction they will expand in. It looks at the different expansion ideas and looks at the possible outcomes for these. It will however only show financial factors affecting the outcome as it analysis solely financial factors.
could u send me the answers for the merits of the decision tables
Decision trees help managers visualize how their choices will play out within the organization. Using a decision tree, management can assess multiple options at once.
Advantages of decision tree analysis: Easy to interpret, Possible scenarios can be easily added, Value of different scenarios can be determined.
The minimum depth of a leaf in a decision tree is typically 0, meaning that a leaf node can be at the same level as its parent node.
SimpleStructuredReduces ambignitycondition and decision relation is clearused for control, testing and planninguseful technique with many application.
In a family tree, use a woman's maiden or birth name rather than her married name. It helps to trace her line of the family. The decision of whether to use birth name or married name for women when creating a family tree is an individual decision that depends on how you want to organize your information. In either case, both names must be recorded somewhere. sometimes both names are included in the family tree layout.
hierarchy
The OR Procedure
The Good Wife - 2009 The Decision Tree 5-10 is rated/received certificates of: USA:TV-14
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