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  1. www.analyticsvidhya.com › blog › 2020Entropy in Machine Learning: Definition, Examples and Uses

    3. Nov. 2023 · In Machine Learning, entropy measures the level of disorder or uncertainty in a given dataset or system. It is a metric that quantifies the amount of information in a dataset, and it is commonly used to evaluate the quality of a model and its ability to make accurate predictions.

  2. machinelearninghowto.com › understanding-entropy-in-machineUnderstanding Entropy in Machine Learning

    22. Dez. 2023 · Entropy is a fundamental concept in information theory that describes the purity or impurity of a dataset. In machine learning, understanding entropy is crucial for building efficient models, especially in algorithms like decision trees. We explore the concept of entropy and its application in machine learning.

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  4. towardsdatascience.com › understanding-entropy-the-goldenUnderstanding Entropy: the Golden Measurement of Machine Learning

    24. Juli 2020 · By using entropy in machine learning, the core component of it — uncertainty and probability — is best represented through ideas like cross-entropy, relative-entropy, and information gain. Entropy is explicit about dealing with the unknown, which is something much to be desired in model-building.

  5. machinelearningmastery.com › what-is-information-entropyA Gentle Introduction to Information Entropy - Machine Learning...

    13. Juli 2020 · Overview. This tutorial is divided into three parts; they are: What Is Information Theory? Calculate the Information for an Event. Calculate the Entropy for a Random Variable. What Is Information Theory? Information theory is a field of study concerned with quantifying information for communication.

  6. datasciencehack.com › blog › 2017/05/02Entropie – Und andere Maße für Unreinheit in Daten

    2. Mai 2017 · Die Entropie als Maß für Unreinheit in Daten. Die Entropie gilt als das am häufigsten eingesetzte Maß für Unreinheit (Impurity) in der Informatik. Es wird in ähnlicher Bedeutung auch in der Thermodynamik und Fluiddynamik eingesetzt, bezieht sich dort nicht auf Daten, sondern auf die Verteilung von Temperatur-/Gas ...

  7. www.mdpi.com › Entropy_Dataset_Machine_LearningEntropy in Real-World Datasets and Its Impact on Machine Learning...

    Entropy 2022, 24 (4), 531; https://doi.org/10.3390/e24040531 - 10 Apr 2022. Cited by 4 | Viewed by 2510. Abstract. Classification is one of the main problems of machine learning, and assessing the quality of classification is one of the most topical tasks, all the more difficult as it depends on many factors.

  8. towardsdatascience.com › the-intuition-behind-shannonsThe intuition behind Shannon’s Entropy - Towards Data Science

    29. Sept. 2018 · The definition of Entropy for a probability distribution (from The Deep Learning Book) But what does this formula mean? For anyone who wants to be fluent in Machine Learning, understanding Shannon’s entropy is crucial.