Module 11 - Decision Tree Flashcards

1
Q

it is a tree shaped diagram used to determine the course of action.

A

Decision Tree

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2
Q

2 Uses of a Decision Tree:

A
  1. Regression Analysis
  2. Classification Analysis
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3
Q

is a statistical method that allows you to examine the relationship between two or more variable of interest

A

Regression Analysis

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4
Q

is a data analysis task that identifies and assigns categories to a collection of data to allow for more accurate analysis.

A

Classification Analysis

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5
Q

3 Advantages of Decision Tree:

A
  1. Simple to understand, interpret, and visualize.
  2. Can handle both numerical and categorical data
  3. Non-linear parameters don’t affect its performance.
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6
Q

3 Disadvantages of Decision Tree

A
  1. Overfitting
  2. High Variance
  3. Low Biased Tree
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7
Q

this occurs when the algorithm captures noise in the data.

A

Overfitting

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8
Q

the model an get unstable due to small variation in the data.

A

High Variance

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9
Q

a highly complicated decision tree tends to have a low bias which makes it difficult for the model to work with new data.

A

Low Biased Tree

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10
Q

(4) Definition of Terms:

A
  1. Entropy
  2. Information Gain
  3. Leaf Node
  4. Root Node
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11
Q

is a measure of randomness of unpredictability of the dataset.

A

Entropy

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12
Q

is a measure of decrease in the entropy after the data set is split.

A

Information Gain

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13
Q

it carries the classification or the decision.

A

Leaf Node

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14
Q

is the topmost decision node in the decision tree.

A

Root Node

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