Figure 1 below is a decision-tree for determining whether an unrelated business is present.

A decision-tree is a series of decision boxes that split a single flow into two or more separate paths.

This is troubleit's a violation of the command decision-tree protocol.

Each Decision-Tree defines two or more Pathways.

Our experiments demonstrate that decision-tree and pattern discovery work well to partition documents into regions and to identify data item respectively.

The script takes the form of a Decision-Tree and is the backbone of the Digital Conversation.

The OECD’s work in this area has resulted in a decision-tree for policy makers that can help when and how to intervene.

The establishment of criteria and the use of a decision-tree were suggested as means to assist in distinguishing proprietary information from what is in the public domain.

• moved to standardize Collaborative Agreements through creation of a collaborative agreement tool that includes a decision-tree and templates that fit varying situations.

Even more debt ceiling fun - David ponders a US default decision-tree, Joseph looks at the Federal Reserve buying Treasuries which have... less than the full faith and credit.

A preliminary decision-tree was developed to assist in suggesting an appropriate UV technology for a given site, which together with a list of various factors and considerations can lead to the selection of an appropriate process.

An example of a decision tree is given in Figure 6.8.

The next two measures use the idea of a decision tree.

As a result, a decision tree is generated for each choice in the process.

A third approach is to construct systems that are based on decision trees.

The statement's truth or otherwise came a bad second in the decision tree.

The first branch on her decision tree was abortion, which she could not bring herself to do.

So each time a different t is set for the decision tree algorithm.

People are able to understand decision tree models after a brief explanation.

Figure 5.3 is a decision tree for a hypothetical development project to develop and market a new product.

The project is broken down into stages which are represented in a decision tree.

At the same time, he created a logical decision tree, addressing the new issues raised.

Decision tree learning is a method commonly used in data mining.

The data structure is similar to a decision tree.

This is because that decision tree model depends on the training data, which could not cover all possible corners.

The result is a decision tree (see Figure 2).

When it comes to credibility, the same decision tree achieved an accuracy of about 86 percent.

Decision trees can be used to optimize an investment portfolio.

Opinions describe ways of satisfying a desire using decision trees.

For example, consider the decision tree below to decide whether to play outside:

Decision trees and data storage are represented in system flow diagrams.

Random forests, in which a large number of decision trees are trained, and the result averaged.

An advantage of decision trees is that they easily handle heterogeneous data.

A decision tree illustrates the actions to be taken at each decision point.

Once the diagnosis is clear, a woman can follow a series of "decision trees" to find out what cancer experts would recommend.

Decision trees used in data mining are of two main types: