IET journal sponsored by the Chinese Association for Artificial Intelligence. Submit today. From machine learning to big data & knowledge engineering, submit your research
- Open Access Advantage
Choose open access for greater
impact, reach and visibility
- Browse Current Issue
Original research, reviews,
case studies, industry articles
- Editorial Board
International expertise in
artificial intelligence
- Journal Overview
Aims and scope,
abstracting and indexing
- Open Access Advantage
Suchergebnisse
Suchergebnisse:
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.
Use in machine learning. Machine learning techniques arise largely from statistics and also information theory. In general, entropy is a measure of uncertainty and the objective of machine learning is to minimize uncertainty. Decision tree learning algorithms use relative entropy to determine the decision rules that govern the data ...
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.
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.
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.
29. Apr. 2022 · An Intuitive Guide To Entropy. Understanding why entropy is a measure of chaos. Aayush Agarwal. ·. Follow. Published in. Towards Data Science. ·. 5 min read. ·. Apr 29, 2022. Prerequisite: An Understanding of Expected Value of Discrete Random Variables. Photo by Siora Photography on Unsplash.
11. Jan. 2019 · Entropy is a measure of disorder or uncertainty and the goal of machine learning models and Data Scientists in general is to reduce uncertainty. Now we know how to measure disorder. Next we need a metric to measure the reduction of this disorder in our target variable/class given additional information( features/independent variables ...
