In machine learning and pattern recognition, a feature is an individual measurable property or characteristic of a phenomenon. Choosing informative, discriminating...
9 KB (1,016 words) - 16:43, 10 June 2024
Machine learning (ML) is a field of study in artificial intelligence concerned with the development and study of statistical algorithms that can learn...
135 KB (14,801 words) - 03:34, 12 August 2024
In machine learning, feature learning or representation learning is a set of techniques that allows a system to automatically discover the representations...
45 KB (5,077 words) - 18:25, 13 May 2024
Feature engineering is a preprocessing step in supervised machine learning and statistical modeling which transforms raw data into a more effective set...
21 KB (2,240 words) - 07:48, 25 June 2024
amenable for machine learning, an expert may have to apply appropriate data pre-processing, feature engineering, feature extraction, and feature selection...
9 KB (1,024 words) - 02:45, 24 July 2024
outline is provided as an overview of and topical guide to machine learning: Machine learning – a subfield of soft computing within computer science that...
41 KB (3,580 words) - 16:15, 14 June 2024
In machine learning, boosting is an ensemble meta-algorithm for primarily reducing bias, variance. It is used in supervised learning and a family of machine...
22 KB (2,305 words) - 03:52, 9 May 2024
In statistics and machine learning, leakage (also known as data leakage or target leakage) is the use of information in the model training process which...
6 KB (685 words) - 21:01, 9 August 2024
Adversarial machine learning is the study of the attacks on machine learning algorithms, and of the defenses against such attacks. A survey from May 2020...
65 KB (7,441 words) - 03:15, 12 August 2024
In statistics and machine learning, ensemble methods use multiple learning algorithms to obtain better predictive performance than could be obtained from...
52 KB (6,606 words) - 18:23, 8 August 2024
Active learning is a special case of machine learning in which a learning algorithm can interactively query a human user (or some other information source)...
19 KB (2,361 words) - 00:11, 17 July 2024
corner or blob Feature (machine learning), in statistics: individual measurable properties of the phenomena being observed Software feature, a distinguishing...
2 KB (304 words) - 04:14, 12 August 2024
In machine learning, support vector machines (SVMs, also support vector networks) are supervised max-margin models with associated learning algorithms...
64 KB (8,980 words) - 00:25, 9 August 2024
Quantum machine learning is the integration of quantum algorithms within machine learning programs. The most common use of the term refers to machine learning...
85 KB (10,301 words) - 07:49, 25 June 2024
In computer science, online machine learning is a method of machine learning in which data becomes available in a sequential order and is used to update...
25 KB (4,740 words) - 03:53, 2 May 2024
The machine learning-based attention method simulates how human attention works by freely assigning appropriate levels of importance to different components...
50 KB (5,535 words) - 09:54, 14 August 2024
In machine learning, a neural network (also artificial neural network or neural net, abbreviated ANN or NN) is a model inspired by the structure and function...
153 KB (16,009 words) - 03:25, 12 August 2024
Geometric feature learning is a technique combining machine learning and computer vision to solve visual tasks. The main goal of this method is to find...
12 KB (2,042 words) - 13:48, 20 April 2024
Transfer learning (TL) is a technique in machine learning (ML) in which knowledge learned from a task is re-used in order to boost performance on a related...
15 KB (1,691 words) - 01:08, 26 July 2024
International Conference on Machine Learning (ICML) is the leading international academic conference in machine learning. Along with NeurIPS and ICLR...
5 KB (377 words) - 03:11, 12 June 2024
Supervised learning (SL) is a paradigm in machine learning where input objects (for example, a vector of predictor variables) and a desired output value...
22 KB (3,012 words) - 13:16, 11 August 2024
Tensor informally refers in machine learning to two different concepts that organize and represent data. Data may be organized in a multidimensional array...
28 KB (3,646 words) - 04:05, 26 July 2024
Fairness in machine learning refers to the various attempts at correcting algorithmic bias in automated decision processes based on machine learning models...
64 KB (9,079 words) - 22:41, 23 July 2024
In machine learning, a learning curve (or training curve) plots the optimal value of a model's loss function for a training set against this loss function...
7 KB (932 words) - 19:02, 13 May 2024
step. Since the range of values of raw data varies widely, in some machine learning algorithms, objective functions will not work properly without normalization...
8 KB (1,041 words) - 02:58, 8 August 2024
Rule-based machine learning (RBML) is a term in computer science intended to encompass any machine learning method that identifies, learns, or evolves...
4 KB (446 words) - 09:40, 6 April 2024
Multimodal learning, in the context of machine learning, is a type of deep learning using multiple modalities of data, such as text, audio, or images....
7 KB (1,903 words) - 14:24, 1 June 2024
In machine learning, normalization is a statistical technique with various applications. There are mainly two forms of normalization, data normalization...
19 KB (3,075 words) - 13:27, 8 August 2024
Federated learning (also known as collaborative learning) is a sub-field of machine learning focusing on settings in which multiple entities (often referred...
51 KB (5,924 words) - 04:38, 28 July 2024
A transformer is a deep learning architecture developed by researchers at Google and based on the multi-head attention mechanism, proposed in a 2017 paper...
93 KB (11,695 words) - 21:43, 13 August 2024