Search results
Results from the WOW.Com Content Network
XAI counters the "black box" tendency of machine learning, where even the AI's designers cannot explain why it arrived at a specific decision. [6] [7] XAI hopes to help users of AI-powered systems perform more effectively by improving their understanding of how those systems reason. [8] XAI may be an implementation of the social right to ...
The field of Explainable AI seeks to provide better explanations from existing algorithms, and algorithms that are more easily explainable, but it is a young and active field. [ 18 ] [ 19 ] Others argue that the difficulties with explainability are due to its overly narrow focus on technical solutions rather than connecting the issue to the ...
scikit-learn (formerly scikits.learn and also known as sklearn) is a free and open-source machine learning library for the Python programming language. [3] It features various classification, regression and clustering algorithms including support-vector machines, random forests, gradient boosting, k-means and DBSCAN, and is designed to interoperate with the Python numerical and scientific ...
In the context of AI, it is particularly used for embedded systems and robotics. Libraries such as TensorFlow C++, Caffe or Shogun can be used. [1] JavaScript is widely used for web applications and can notably be executed with web browsers. Libraries for AI include TensorFlow.js, Synaptic and Brain.js. [6]
Xai, XAI or xAI may refer to: Explainable artificial intelligence, in artificial intelligence technology; Xai-Xai, a city in the south of Mozambique; XAI, the IATA airport code for Xinyang Minggang Airport, in Xinyang, China; xai, the ISO 639-3 language code of Kaimbé language, an extinct language in Brazil.
In machine learning and pattern recognition, a feature is an individual measurable property or characteristic of a data set. [1] Choosing informative, discriminating, and independent features is crucial to produce effective algorithms for pattern recognition, classification, and regression tasks.
[1] [3] ALE requires more and more uniformly distributed observations than PDP so that the conditional distribution can be reliably determined. The technique may produce inadequate results if the data is highly sparse, which is more common with high-dimensional data ( curse of dimensionality ).
Open-source artificial intelligence is an AI system that is freely available to use, study, modify, and share. [1] These attributes extend to each of the system's components, including datasets, code, and model parameters, promoting a collaborative and transparent approach to AI development. [1]