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AI that learns decision rules from data
Rule-based machine learning (RBML) is a term in computer science intended to encompass any machine learning method that identifies, learns, or evolves
Rule-based_machine_learning
Subset of artificial intelligence
prediction. Rule-based machine learning approaches include learning classifier systems, association rule learning, and artificial immune systems. Based on the
Machine_learning
Overview of and topical guide to machine learning
algorithm Reinforcement learning Repeated incremental pruning to produce error reduction (RIPPER) Rprop Rule-based machine learning Self-organizing map Skill
Outline_of_machine_learning
Method for discovering interesting relations between variables in databases
Association rule learning is a rule-based machine learning method for discovering interesting relations between variables in large databases. It is intended
Association_rule_learning
Paradigm of rule-based machine learning methods
Learning classifier systems, or LCS, are a paradigm of rule-based machine learning methods that combine a discovery component (e.g. typically a genetic
Learning_classifier_system
Class of rule-based machine learning systems
Artificial immune systems (AIS) are a class of rule-based machine learning systems inspired by the principles and processes of the vertebrate immune system
Artificial_immune_system
Process of automating the application of machine learning
raw dataset to building a machine learning model ready for deployment. AutoML was proposed as an artificial intelligence-based solution to the growing challenge
Automated_machine_learning
Type of computer system
Expert systems Rewriting RuleML List of rule-based languages Learning classifier system Rule-based machine learning Rule-based modeling Crina Grosan; Ajith
Rule-based_system
Artificial neural network algorithm
An artificial neural network's learning rule or learning process is a method, mathematical logic or algorithm which improves the network's performance
Learning_rule
Machine learning strategy
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)
Active learning (machine learning)
Active_learning_(machine_learning)
Ensemble learning method
In machine learning (ML), boosting is an ensemble learning method that combines a set of less accurate models (called "weak learners") to create a single
Boosting_(machine_learning)
Research field that lies at the intersection of machine learning and computer security
Adversarial machine learning is the study of the attacks on machine learning algorithms, and of the defenses against such attacks. Machine learning techniques
Adversarial_machine_learning
Academic conference in machine learning
The International Conference on Machine Learning (ICML) is an international academic conference in machine learning held annually since 1980. It is the
International Conference on Machine Learning
International_Conference_on_Machine_Learning
page is a timeline of machine learning. Major discoveries, achievements, milestones, and other major events in machine learning are included. History
Timeline_of_machine_learning
Machine learning technique
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
Transfer_learning
Academic journal
The Journal of Machine Learning Research is a peer-reviewed open access scientific journal covering machine learning. It was established in 2000 and the
Journal of Machine Learning Research
Journal_of_Machine_Learning_Research
Machine learning technique
In machine learning, attention is a method that determines the importance of each component in a sequence relative to the other components in that sequence
Attention_(machine_learning)
Algorithm for modelling sequential data
In deep learning, the transformer is a family of artificial neural network architectures based on the multi-head attention mechanism, in which text is
Transformer_(deep_learning)
Interdisciplinary research area
Quantum machine learning (QML) is the study of quantum algorithms for machine learning. It often refers to quantum algorithms for machine learning tasks
Quantum_machine_learning
Concept in machine learning
In statistics and machine learning, leakage (also known as data leakage or target leakage) refers to the use of information during model training that
Leakage_(machine_learning)
Statistics and machine learning technique
In statistics and machine learning, ensemble methods use multiple learning algorithms to obtain better predictive performance than could be obtained from
Ensemble_learning
Area of machine learning
Rule induction is an area of machine learning in which formal rules are extracted from a set of observations. The rules extracted may represent a full
Rule_induction
Machine learning technique
In machine learning, reinforcement learning from human feedback (RLHF) is a technique to align an intelligent agent with human preferences. It involves
Reinforcement learning from human feedback
Reinforcement_learning_from_human_feedback
Field of machine learning
Reinforcement learning is one of the three basic machine learning paradigms, alongside supervised learning and unsupervised learning. While supervised learning and
Reinforcement_learning
Method of machine learning
trees. Machine Learning, 4(2): 161-186, 1989 Ferrer-Troyano, Francisco, Jesus S. Aguilar-Ruiz, and Jose C. Riquelme. Incremental rule learning based on example
Incremental_learning
Categorization of data using statistics
membership probabilities – Machine learning problemPages displaying short descriptions of redirect targets Classification rule Compound term processing
Statistical_classification
control, procedural content generation (PCG) and deep learning-based content generation. Machine learning is a subset of artificial intelligence that uses
Machine learning in video games
Machine_learning_in_video_games
Machine learning technique
In machine learning, normalization is a statistical technique with various applications. There are two main forms of normalization, namely data normalization
Normalization (machine learning)
Normalization_(machine_learning)
AI whose outputs can be understood by humans
(XAI), generally overlapping with interpretable AI or explainable machine learning (XML), is a field of research that explores methods that provide humans
Explainable artificial intelligence
Explainable_artificial_intelligence
Set of methods for supervised statistical learning
In machine learning, support vector machines (SVMs, also support vector networks) are supervised max-margin models with associated learning algorithms
Support_vector_machine
Tuning parameter (hyperparameter) in optimization
In machine learning and statistics, the learning rate is a tuning parameter in an optimization algorithm that determines the step size at each iteration
Learning_rate
machine learning (ML) research and have been cited in peer-reviewed academic journals. Datasets are an integral part of the field of machine learning
List of datasets for machine-learning research
List_of_datasets_for_machine-learning_research
Machine learning that combines deep learning and reinforcement learning
Deep reinforcement learning (deep RL) is a subfield of machine learning that combines reinforcement learning (RL) and deep learning. RL considers the problem
Deep_reinforcement_learning
Model-free reinforcement learning algorithm
Q-learning is a reinforcement learning algorithm that trains an agent to assign values to its possible actions based on its current state, without requiring
Q-learning
Academic conference in machine learning
The International Conference on Learning Representations (ICLR) is a machine learning conference typically held in late April or early May each year.
International Conference on Learning Representations
International_Conference_on_Learning_Representations
Machine learning method
Logic learning machine (LLM) is a machine learning method based on the generation of intelligible rules. LLM is an efficient implementation of the Switching
Logic_learning_machine
Computational model used in machine learning
In machine learning, a neural network (NN) or neural net, is a computational model inspired by the structure and functions of biological neural networks
Neural network (machine learning)
Neural_network_(machine_learning)
Paradigm in machine learning that uses no classification labels
Unsupervised learning is a framework in machine learning where, in contrast to supervised learning, algorithms learn patterns exclusively from unlabeled
Unsupervised_learning
Method of machine learning
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
Online_machine_learning
Open-source machine-learning software library
open-source machine-learning software library and ecosystem written in Julia. Its current stable release is v0.16.5 . It has a layer-stacking-based interface
Flux (machine-learning framework)
Flux_(machine-learning_framework)
Framework for machine learning
Statistical learning theory is a framework for machine learning drawing from the fields of statistics and functional analysis. Statistical learning theory
Statistical_learning_theory
Use of pre-translated texts as linguistic corpuses in computing
implementation of a case-based reasoning approach to machine learning. At the foundation of example-based machine translation is the idea of translation by analogy
Example-based machine translation
Example-based_machine_translation
Machine learning technique
Mixture of experts (MoE) is a machine learning technique where multiple expert networks (learners) are used to divide a problem space into homogeneous
Mixture_of_experts
Term in educational psychology
abstract concept learning are topics like religion and ethics. Abstract-concept learning is seeing the comparison of the stimuli based on a rule (e.g., identity
Concept_learning
Decentralized machine learning
Federated learning (also known as collaborative learning) is a machine learning technique in a setting where multiple entities (often called clients)
Federated_learning
Competitive algorithm for searching a problem space
Propagation of schema Universal Darwinism Metaheuristics Learning classifier system Rule-based machine learning Pétrowski, Alain; Ben-Hamida, Sana (2017). Evolutionary
Genetic_algorithm
Type of statistical inference
Semi-supervised learning Case-based reasoning k-nearest neighbor algorithm Support vector machine Vapnik, Vladimir (2006). "Estimation of Dependences Based on Empirical
Transduction (machine learning)
Transduction_(machine_learning)
Computer system emulating human expert
to AI were required instead of rule-based technologies. These new approaches are based on the use of machine learning techniques, along with the use of
Expert_system
Technique for the generative modeling of a continuous probability distribution
In machine learning, diffusion models, also known as diffusion-based generative models or score-based generative models, are a class of latent variable
Diffusion_model
Plot of machine learning model performance over time or experience
In machine learning (ML), a learning curve (or training curve) is a graphical representation that shows how a model's performance on a training set (and
Learning curve (machine learning)
Learning_curve_(machine_learning)
Machine learning paradigm
Self-supervised learning (SSL) is a paradigm in machine learning where a model is trained on a task using the data itself to generate supervisory signals
Self-supervised_learning
Type of feedforward neural network
including text, images and audio. CNNs are the de-facto standard in deep learning-based approaches to computer vision and image processing, and have only recently
Convolutional_neural_network
Measurable property or characteristic
In machine learning and pattern recognition, a feature is an individual measurable property or characteristic of a data set. Choosing informative, discriminating
Feature_(machine_learning)
Use of machine learning to rank items
Learning to rank (LTR) or machine-learned ranking (MLR) is the application of machine learning, often supervised, semi-supervised or reinforcement learning
Learning_to_rank
Game genre
problem solving. Game-based learning (GBL) is a type of game play that has defined learning outcomes. Generally, game-based learning is designed to balance
Educational_game
Theory of machine learning
Theoretical results in machine learning often focus on a type of inductive learning known as supervised learning. In supervised learning, an algorithm is provided
Computational_learning_theory
Technique in machine learning
Curriculum learning is a technique in machine learning in which a model is trained on examples of increasing difficulty, where the definition of "difficulty"
Curriculum_learning
Programming paradigm based on formal logic
languages Programmable logic controller R++ Reasoning system Rule-based machine learning Satisfiability Syntax and semantics of logic programming Tärnlund
Logic_programming
Computer programming concept
the value function for the current state using the rule: V ( S t ) ← ( 1 − α ) V ( S t ) + α ⏟ learning rate [ R t + 1 + γ V ( S t + 1 ) ⏞ The TD target
Temporal_difference_learning
Machine learning methods using multiple input modalities
Multimodal learning is a type of deep learning that integrates and processes multiple types of data, referred to as modalities, such as text, audio, images
Multimodal_learning
Type of artificial neural network
learning machines are feedforward neural networks for classification, regression, clustering, sparse approximation, compression and feature learning with
Extreme_learning_machine
Method in machine learning
called bagging (from bootstrap aggregating) or bootstrapping, is a machine learning (ML) ensemble meta-algorithm designed to improve the stability and
Bootstrap_aggregating
Software for understanding biological data
Machine learning in bioinformatics is the application of machine learning algorithms to bioinformatics, including genomics, proteomics, microarrays, systems
Machine learning in bioinformatics
Machine_learning_in_bioinformatics
Machine-learning process
in machine learning of learning a formal grammar (usually as a collection of re-write rules or productions or alternatively as a finite-state machine or
Grammar_induction
Type of feedforward neural network
In deep learning, a multilayer perceptron (MLP) is a kind of modern feedforward neural network consisting of fully connected neurons with nonlinear activation
Multilayer_perceptron
Type of large language model
faster model or slower reasoning model based on the provided task. During the 2010s, improved machine learning algorithms, more powerful computers, and
Generative pre-trained transformer
Generative_pre-trained_transformer
Branch of machine learning
In machine learning, deep learning (DL) focuses on utilizing multilayered neural networks to perform tasks such as classification, regression, and representation
Deep_learning
Use of technology in education to enhance learning and teaching
encompasses several domains, including learning theory, computer-based training, online learning, and mobile learning (m-learning). The Association for Educational
Educational_technology
Class of artificial neural network
Boltzmann machines, in particular the gradient-based contrastive divergence algorithm. Restricted Boltzmann machines can also be used in deep learning networks
Restricted_Boltzmann_machine
Measurement of algorithmic bias
Fairness in machine learning (ML) refers to the various attempts to correct algorithmic bias in automated decision processes based on ML models. Decisions
Fairness_(machine_learning)
Artificial neural networks (ANNs) are models created using machine learning to perform a number of tasks. While the computational implementations of ANNs
History of artificial neural networks
History_of_artificial_neural_networks
Type of stochastic recurrent neural network
LeCun in cognitive sciences communities, particularly in machine learning, as part of "energy-based models" (EBM), because Hamiltonians of spin glasses as
Boltzmann_machine
Learner centric pedagogy
Design-based learning (DBL), also known as design-based instruction, is an inquiry-based form of learning, or pedagogy, that is based on integration of
Design-based_learning
Computer program used to provide artificial intelligence
Learning Classifier System Logic programming Inference engine L-system OPS5 Production Rule Representation Rete algorithm Rule-based machine learning
Production system (computer science)
Production_system_(computer_science)
Learner centric pedagogy
instead of in a subject-based approach. Phenomenon-based learning includes both topical learning (also known as topic-based learning or instruction), where
Phenomenon-based_learning
Set of learning techniques in machine learning
In machine learning (ML), feature learning or representation learning is a set of techniques that allow a system to automatically discover the representations
Feature_learning
Property of a model
In statistics and machine learning, the bias–variance tradeoff describes the relationship between a model's complexity, the accuracy of its predictions
Bias–variance_tradeoff
Machine learning paradigm
In machine learning, supervised learning (SL) is a type of machine learning paradigm where an algorithm learns to map input data to a specific output based
Supervised_learning
platforms, and tools used for machine learning, deep learning, natural language processing, computer vision, reinforcement learning, artificial general intelligence
Lists of open-source artificial intelligence software
Lists_of_open-source_artificial_intelligence_software
Method in natural language processing
Data" (PDF). Journal of Machine Learning Research. Qureshi, M. Atif; Greene, Derek (2018-06-04). "EVE: explainable vector based embedding technique using
Word_embedding
Process of acquiring new knowledge
humans, other animals, and some machines. There is also evidence for some kind of learning in certain plants. Some learning is immediate, induced by a single
Learning
Extracting features from raw data for machine learning
Feature engineering is a preprocessing step in supervised machine learning and statistical modeling which transforms raw data into a more effective set
Feature_engineering
Software user interface
context of machine learning.It is also used in conversational AI to manage complex interactions that require human empathy. In machine learning, HITL is
Human-in-the-loop
Explanation-based learning (EBL) is a form of machine learning that exploits a very strong, or even perfect, domain theory (i.e. a formal theory of an
Explanation-based_learning
Machine learning model for vision processing
Framework for Attention-based Permutation-Invariant Neural Networks". Proceedings of the 36th International Conference on Machine Learning. PMLR: 3744–3753.
Vision_transformer
Algorithm for supervised learning of binary classifiers
In machine learning, the perceptron is an algorithm for supervised learning of binary classifiers. A binary classifier is a function that can decide whether
Perceptron
Machine learning calibration technique
In machine learning, Platt scaling or Platt calibration is a way of transforming the outputs of a classification model into a probability distribution
Platt_scaling
Subfield of machine learning
Meta-learning is a subfield of machine learning where automatic learning algorithms are applied to metadata about machine learning experiments. As of
Meta-learning (computer science)
Meta-learning_(computer_science)
Research field in deep learning
deep learning (TDL) is a research field that extends deep learning to handle complex, non-Euclidean data structures. Traditional deep learning models
Topological_deep_learning
Models used to produce word embeddings
sequences, this representation can be widely used in applications of machine learning in proteomics and genomics. The results suggest that BioVectors can
Word2vec
List of concepts in artificial intelligence
immune system (AIS) A class of computationally intelligent, rule-based machine learning systems inspired by the principles and processes of the vertebrate
Glossary of artificial intelligence
Glossary_of_artificial_intelligence
Deep learning method
A generative adversarial network (GAN) is a class of machine learning frameworks and a prominent framework for approaching generative artificial intelligence
Generative adversarial network
Generative_adversarial_network
Model-free reinforcement learning algorithm
Proximal policy optimization (PPO) is a reinforcement learning (RL) algorithm for training an intelligent agent. Specifically, it is a policy gradient
Proximal_policy_optimization
Machine learning problem
In machine learning, a probabilistic classifier is a classifier that is able to predict, given an observation of an input, a probability distribution over
Probabilistic_classification
Statistical model used in machine learning
A flow-based generative model is a generative model used in machine learning that explicitly models a probability distribution by leveraging normalizing
Flow-based_generative_model
Automated recognition of patterns and regularities in data
retrieval, bioinformatics, data compression, computer graphics and machine learning. Pattern recognition has its origins in statistics and engineering;
Pattern_recognition
Artificial neural network that mimics neurons
unsuitable for gradient-based optimization. Approaches to resolving it include: resorting to entirely biologically inspired local learning rules for the hidden
Spiking_neural_network
Machine learning algorithm
Decision tree learning is a supervised learning approach used in statistics, data mining and machine learning. In this formalism, a classification or
Decision_tree_learning
2020 text-generating language model
increase in the amount of digitized material have fueled a revolution in machine learning. New techniques in the 2010s resulted in "rapid improvements in tasks"
GPT-3
Machine learning software
Tanagra is a free suite of machine learning software for research and academic purposes developed by Ricco Rakotomalala at the Lumière University Lyon
Tanagra_(machine_learning)
RULE BASED-MACHINE-LEARNING
RULE BASED-MACHINE-LEARNING
Girl/Female
Bengali, Indian
Machine
Female
Scottish
Feminine form of Scottish Lachlan, LACHINA means "lake-land."
Female
Hawaiian
Hawaiian name MAHINA means "moon; moonlight."
Male
French
French form of Latin Macarius, MACAIRE means "blessed."
Boy/Male
French, German, Latin
Famous Wolf
Female
Native American
Native American Hopi name KACHINA means "sacred dancer; spirit."
Girl/Female
Australian, Japanese
Child of Machi
Surname or Lastname
English
English : from the medieval personal name Roul (see Rollo, Rolf).Scottish : habitational name from a place in Roxburghshire, so named from the stream on which it stands. This name is of uncertain origin, possibly from Welsh rhull ‘hasty’, ‘rash’.Probably an altered spelling of German Ruhl.
Surname or Lastname
English
English : variant spelling of Machen.Spanish (MachÃn) : probably a nickname from machÃn ‘boor’, ‘lout’, often applied to a blacksmith’s apprentice.French : nickname from Old French machin ‘scheming’.
Girl/Female
African, Arabic, Australian, Latin
Ruler; Commander or Leader
Female
French
Feminine form of French Marin, MARINE means "of the sea."
Girl/Female
Norse
Born during Yule.
Female
German
German form of Scottish Malvina, MALWINE means "smooth-brow."
Male
English
Pet form of English Sacheverell, SACHIE means "roe-buck leap."
Male
Scottish
Pet form of Scottish Gaelic Lachlann, LACHIE means "lake-land."
Female
French
French feminine form of Latin Martinus, MARTINE means "of/like Mars."Â
Male
Hindi/Indian
(सचिन) Hindi myth name borne by Indra, SACHIN means "pure."
Boy/Male
American, Australian
Weighing Machine
Female
English
Variant spelling of English Maureen, MAURINE means "obstinacy, rebelliousness" or "their rebellion."
Boy/Male
Latin French
Ruler.
RULE BASED-MACHINE-LEARNING
RULE BASED-MACHINE-LEARNING
Girl/Female
Muslim
Garden, Gulshan
Girl/Female
African, American, Australian, British, Christian, English, Jamaican, Latin
Sweet Smelling Flower; Garden's Flower; Gardenia Flower
Boy/Male
Hindu, Indian, Marathi
Cool; Nectar
Boy/Male
Egyptian
Only son.
Boy/Male
Afghan, African, Arabic, French, German, Hebrew, Hindu, Indian, Malaysian, Marathi, Muslim, Pashtun, Sindhi, Swahili, Tamil, Telugu, Turkish
Gentle; Pleasant; Caress or Gentle Slap; Generous; Enigmatic; Gracious; Fine; Refined; Kind
Girl/Female
Indian, Tamil
Always Smiling
Girl/Female
Hindu
Evening, Twilight, Dusk
Girl/Female
Australian, Indian, Irish, Tamil, Telugu
Sun
Boy/Male
Hindu
It is a one of Lord shiva`s name
Boy/Male
Indian
Method, Way, Mode, Manner, One who crosses the river of life, Morning star
RULE BASED-MACHINE-LEARNING
RULE BASED-MACHINE-LEARNING
RULE BASED-MACHINE-LEARNING
RULE BASED-MACHINE-LEARNING
RULE BASED-MACHINE-LEARNING
n.
To mark with lines made with a pen, pencil, etc., guided by a rule or ruler; to print or mark with lines by means of a rule or other contrivance effecting a similar result; as, to rule a sheet of paper of a blank book.
n.
To establish or settle by, or as by, a rule; to fix by universal or general consent, or by common practice.
imp. & p. p.
of Rule
a.
Of or pertaining to machines.
v. t.
To subject to the action of machinery; to effect by aid of machinery; to print with a printing machine.
n.
One who or operates a machine; a machinist.
v. i.
To lay down and settle a rule or order of court; to decide an incidental point; to enter a rule.
n.
A machine, used in factories, for spinning cotton, wool, etc., into yarn or thread and winding it into cops; -- called also jenny and mule-jenny.
imp. & p. p.
of Machine
a.
That which is prescribed or laid down as a guide for conduct or action; a governing direction for a specific purpose; an authoritative enactment; a regulation; a prescription; a precept; as, the rules of various societies; the rules governing a school; a rule of etiquette or propriety; the rules of cricket.
imp. & p. p.
of Base
n.
The working parts of a machine, engine, or instrument; as, the machinery of a watch.
n.
A combination of persons acting together for a common purpose, with the agencies which they use; as, the social machine.
a.
Having a base, or having as a base; supported; as, broad-based.
a.
A composing rule. See under Conposing.
v. i.
To keep within a (certain) range for a time; to be in general, or as a rule; as, prices ruled lower yesterday than the day before.
n.
Machines, in general, or collectively.
n.
Wearing, or protected by, bases.
n.
To require or command by rule; to give as a direction or order of court.
n.& v.
Rule.