Artificial intelligence and Pruning (decision trees)

Shortcuts: Differences, Similarities, Jaccard Similarity Coefficient, References.

Difference between Artificial intelligence and Pruning (decision trees)

Artificial intelligence vs. Pruning (decision trees)

Artificial intelligence (AI, also machine intelligence, MI) is intelligence demonstrated by machines, in contrast to the natural intelligence (NI) displayed by humans and other animals. Pruning is a technique in machine learning that reduces the size of decision trees by removing sections of the tree that provide little power to classify instances.

Similarities between Artificial intelligence and Pruning (decision trees)

Artificial intelligence and Pruning (decision trees) have 5 things in common (in Unionpedia): Artificial neural network, Decision tree learning, Machine learning, Overfitting, Statistical classification.

Artificial neural network

Artificial neural networks (ANNs) or connectionist systems are computing systems vaguely inspired by the biological neural networks that constitute animal brains.

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Decision tree learning

Decision tree learning uses a decision tree (as a predictive model) to go from observations about an item (represented in the branches) to conclusions about the item's target value (represented in the leaves).

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Machine learning

Machine learning is a subset of artificial intelligence in the field of computer science that often uses statistical techniques to give computers the ability to "learn" (i.e., progressively improve performance on a specific task) with data, without being explicitly programmed.

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Overfitting

In statistics, overfitting is "the production of an analysis that corresponds too closely or exactly to a particular set of data, and may therefore fail to fit additional data or predict future observations reliably".

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Statistical classification

In machine learning and statistics, classification is the problem of identifying to which of a set of categories (sub-populations) a new observation belongs, on the basis of a training set of data containing observations (or instances) whose category membership is known.

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The list above answers the following questions

What Artificial intelligence and Pruning (decision trees) have in common
What are the similarities between Artificial intelligence and Pruning (decision trees)

Artificial intelligence and Pruning (decision trees) Comparison

Artificial intelligence has 543 relations, while Pruning (decision trees) has 10. As they have in common 5, the Jaccard index is 0.90% = 5 / (543 + 10).

References

This article shows the relationship between Artificial intelligence and Pruning (decision trees). To access each article from which the information was extracted, please visit:

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