Question

name: __________ date: __________
vocabulary
define the below vocabulary words and use them in a sentence. do not cut and paste.
decision tree
noun
predictions
noun
flowchart
noun
root node
noun
internal nodes
noun
leaf node
noun
classification tree
noun

Explanation:

This is a vocabulary - defining task. For each term, we need to provide a clear definition and then use it in a sentence.

1. decision tree

• Definition: A decision tree is a graphical representation (like a tree - structured model) used in machine learning, statistics, and other fields. It is used to make decisions or predictions by splitting data based on different attributes or features. The tree has nodes (root, internal, leaf) where each internal node represents a test on an attribute, each branch represents the outcome of the test, and each leaf node represents a class label or a decision.
• Sentence: We used a decision tree to analyze the customer data and predict their purchasing behavior.

2. predictions

• Definition: Predictions are statements or estimates about what will happen in the future. They are often based on data analysis, patterns, or previous experiences. In the context of data science, predictions can be made about various phenomena like sales, weather, or the behavior of a system.
• Sentence: The weather forecaster's predictions about the upcoming storm helped the residents prepare in advance.

3. flowchart

• Definition: A flowchart is a diagram that represents a process or a set of steps in a sequential order. It uses different symbols (like rectangles for processes, diamonds for decisions, and arrows for the flow of the process) to show how a task or a system works, from the start to the end.
• Sentence: The software developer created a flowchart to explain the steps of the new program's execution to the team.

4. root node

• Definition: In a tree - like structure (such as a decision tree), the root node is the top - most node. It is the starting point of the tree. All other nodes (internal and leaf nodes) in the tree are derived from the root node through a series of splits or branches.
• Sentence: The root node of our decision tree was based on the most important feature of the dataset.

5. internal nodes

• Definition: In a tree structure (for example, a decision tree), internal nodes are the nodes that are not the root node and not the leaf nodes. Each internal node represents a test on an attribute (in the case of a decision tree) and has branches that lead to other nodes (either other internal nodes or leaf nodes).
• Sentence: The internal nodes of the classification tree were used to further split the data into more specific subsets.

6. leaf node

• Definition: In a tree - structured model (like a decision tree), a leaf node is a node at the end of a branch. It does not have any child nodes. In a decision tree used for classification, a leaf node typically represents a class label, and in a regression - based decision tree, it represents a value.
• Sentence: Each leaf node in our decision tree gave us a specific prediction about the outcome of the data sample.

7. classification tree

• Definition: A classification tree is a type of decision tree that is specifically used for classification tasks. In a classification tree, the goal is to assign a data sample to one of several predefined classes. The tree is built by splitting the data based on attributes in a way that maximizes the separation between the different classes.
• Sentence: We employed a classification tree to classify the emails as either spam or non - spam.

Answer:

• decision tree: Defined as a graphical tree - structured model for decision - making/prediction by splitting data; Sentence: We used a decision tree to analyze the customer data and predict their purchasing behavior.
• predictions: Defined as future - oriented statements/estimates based on data/patterns; Sentence: The weather forecaster's predictions about the upcoming storm helped the residents prepare in advance.
• flowchart: Defined as a diagram showing a process's sequential steps with symbols; Sentence: The software developer created a flowchart to explain the steps of the new program's execution to the team.
• root node: Defined as the top - most, starting node in a tree structure; Sentence: The root node of our decision tree was based on the most important feature of the dataset.
• internal nodes: Defined as non - root, non - leaf nodes in a tree, representing attribute tests; Sentence: The internal nodes of the classification tree were used to further split the data into more specific subsets.
• leaf node: Defined as end - of - branch nodes in a tree, with no child nodes; Sentence: Each leaf node in our decision tree gave us a specific prediction about the outcome of the data sample.
• classification tree: Defined as a decision tree for classifying data into predefined classes; Sentence: We employed a classification tree to classify the emails as either spam or non - spam.