G06N   3/00  \	0	0	5B278	G06N   3/00	21	ʪŪǥ˴Ť׻֡Σ	Computing arrangements based on biological models [7, 2006.01, 2023.01]
G06N   3/00 120 \	1	1	5B278	G06N   3/00	20	ʬҷ׻ʤʬҡޤϺ˦ѤΡʣģΣѤΣǣΣ˥塼ѤΣǣΣ	Biomolecular computers, i.e. using biomolecules, proteins or cells (using DNA G06N3/12, using neurons G06N3/06)
G06N   3/004  \	1	1	5B278	G06N   3/004	1083	͹̿ʤ̿Τ򥷥ߥ졼Ȥ׻֡Σ	Artificial life, i.e. computing arrangements simulating life [2023.01]
G06N   3/006  \	2	2	5B278	G06N   3/006	1116	ߥ졼Ȥ줿ŪʸĿͤޤϽ̿Τ˴ŤΡʤҲ񥷥ߥ졼ޤγҷŬΣУӣϡϡΣ	based on simulated virtual individual or collective life forms, e.g. social simulations or particle swarm optimisation [PSO] [2023.01]
G06N   3/008  \	2	2	5B278	G06N   3/008	396	Ū̿ΤƸ뤿˥ߥ졼Ȥ줿ˤä椵줿ʪŪʼΤ˴ŤΡ㡥ڥåȤޤϿʹ֤γޤϹưƸܥåȤ˴ŤΡΣ	based on physical entities controlled by simulated intelligence so as to replicate intelligent life forms, e.g. based on robots replicating pets or humans in their appearance or behaviour [2023.01]
G06N   3/02  \	1	1	5B278	G06N   3/02	1893	˥塼ͥåȥΣ	Neural networks [7, 2006.01]
G06N   3/04  \	2	2	5B278	G06N   3/04	2736	ƥ㡤㡥ֹ¤Σ	Architecture, e.g. interconnection topology [7, 2006.01, 2023.01]
G06N   3/04 100 \	3	3	5B278	G06N   3/04	159	ե˥塼ͥåȥΣ	Graph neural networks
G06N   3/042  \	3	3	5B278	G06N   3/042	163	μ١˥塼ͥåȥ˥塼ͥåȥŪɽΣ	Knowledge-based neural networks; Logical representations of neural networks [2023.01]
G06N   3/043  \	3	3	5B278	G06N   3/043	341	եեСåפޤϥե˴ŤΡ㡥Ŭ˥塼եƥΣΣƣɣӡϡΣ	based on fuzzy logic, fuzzy membership or fuzzy inference, e.g. adaptive neuro-fuzzy inference systems [ANFIS] [2023.01]
G06N   3/044  \	3	3	5B278	G06N   3/044	787	ꥫȥͥåȥ㡥ۥåץեɡͥåȥΣ	Recurrent networks, e.g. Hopfield networks [2023.01]
G06N   3/044 100 \	4	4	5B278	G06N   3/044	148	ꥶХԥ塼ƥ󥰡Σ	Reservoir computing
G06N   3/0442  \	4	4	5B278	G06N   3/0442	174	ޤϥȤħͭΡ㡥ĹûΣ̣ӣԣ͡Ϥޤϥդ󵢷˥åȡΣǣңաϡΣ	characterised by memory or gating, e.g. long short-term memory [LSTM] or gated recurrent units [GRU] [2023.01]
G06N   3/045  \	3	3	5B278	G06N   3/045	1165	ͥåȥȤ߹碌Σ	Combinations of networks [2023.01]
G06N   3/0455  \	4	4	5B278	G06N   3/0455	528	ȥ󥳡ͥåȥ󥳡ǥͥåȥΣ	Auto-encoder networks; Encoder-decoder networks [2023.01]
G06N   3/0464  \	3	3	5B278	G06N   3/0464	1011	߹ߥͥåȥΣãΣΡãΣϡΣ	Convolutional networks [CNN, ConvNet] [2023.01]
G06N   3/047  \	3	3	5B278	G06N   3/047	82	ΨŪޤϳΨŪͥåȥΣ	Probabilistic or stochastic networks [2023.01]
G06N   3/0475  \	3	3	5B278	G06N   3/0475	765	ͥåȥΣ	Generative networks [2023.01]
G06N   3/048  \	3	3	5B278	G06N   3/048	184	ؿΣ	Activation functions [2023.01]
G06N   3/049  \	3	3	5B278	G06N   3/049	486	Ūʥ˥塼ͥåȥ㡥ٱǡ˥塼ưޤϥѥ륹ϡΣ	Temporal neural networks, e.g. delay elements, oscillating neurons or pulsed inputs [2023.01]
G06N   3/0495  \	3	3	5B278	G06N   3/0495	433	̻Ҳ줿ͥåȥѡ줿ͥåȥ̤줿ͥåȥΣ	Quantised networks; Sparse networks; Compressed networks [2023.01]
G06N   3/0499  \	3	3	5B278	G06N   3/0499	258	եɥեɥͥåȥΣ	Feedforward networks [2023.01]
G06N   3/06  \	2	2	5B278	G06N   3/06	314	ʪŪʼ¸ʤ˥塼ͥåȥ˥塼ޤϥ˥塼ǤΥϡɥΣ	Physical realisation, i.e. hardware implementation of neural networks, neurons or parts of neurons [7, 2006.01]
G06N   3/063  \	3	3	5B278	G06N   3/063	1999	ŻŪʤѤΡΣ	using electronic means [7, 2006.01, 2023.01]
G06N   3/065  \	4	4	5B278	G06N   3/065	485	ʥʡΣ	Analogue means [2023.01]
G06N   3/067  \	3	3	5B278	G06N   3/067	295	ŪʤѤΡΣ	using optical means [7, 2006.01]
G06N   3/08  \	2	2	5B278	G06N   3/08	4109	ؽˡΣ	Learning methods [7, 2006.01, 2023.01]
G06N   3/082  \	3	3	5B278	G06N   3/082	437	ƥѹΡ㡥ΡɤޤϷɲáޤ̵ΡΣ	modifying the architecture, e.g. adding, deleting or silencing nodes or connections [2023.01]
G06N   3/084  \	3	3	5B278	G06N   3/084	2302	Хåץѥ㡥۹߲ˡѤΡΣ	Backpropagation, e.g. using gradient descent [2023.01]
G06N   3/086  \	3	3	5B278	G06N   3/086	129	ʲŪ르ꥺѤΡ㡥Ū르ꥺޤϰŪץߥ󥰡Σ	using evolutionary algorithms, e.g. genetic algorithms or genetic programming [2023.01]
G06N   3/088  \	3	3	5B278	G06N   3/088	515	դʤؽ㡥ؽΣ	Non-supervised learning, e.g. competitive learning [2023.01]
G06N   3/0895  \	3	3	5B278	G06N   3/0895	192	嶵դؽ㡥ȾդؽޤϼʶդؽΣ	Weakly supervised learning, e.g. semisupervised or self-supervised learning [2023.01]
G06N   3/09  \	3	3	5B278	G06N   3/09	789	դؽΣ	Supervised learning [2023.01]
G06N   3/091  \	3	3	5B278	G06N   3/091	37	ǽưؽΣ	Active learning [2023.01]
G06N   3/092  \	3	3	5B278	G06N   3/092	357	ؽΣ	Reinforcement learning [2023.01]
G06N   3/094  \	3	3	5B278	G06N   3/094	237	ŨŪؽΣ	Adversarial learning [2023.01]
G06N   3/096  \	3	3	5B278	G06N   3/096	267	žܳؽΣ	Transfer learning [2023.01]
G06N   3/098  \	3	3	5B278	G06N   3/098	419	ʬؽ㡥ϢؽΣ	Distributed learning, e.g. federated learning [2023.01]
G06N   3/0985  \	3	3	5B278	G06N   3/0985	192	ϥѡѥ᡼Ŭ᥿ؽؽˡγؽΣ	Hyperparameter optimisation; Meta-learning; Learning-to-learn [2023.01]
G06N   3/10  \	2	2	5B278	G06N   3/10	413	󥿡եץߥ󥰸ޤϥեȥγȯåȡ㡥˥塼ͥåȥ򥷥ߥ졼Ȥ뤿ΤΡΣ	Interfaces, programming languages or software development kits, e.g. for simulating neural networks [7, 2006.01]
G06N   3/12  \	1	1	5B278	G06N   3/12	137	ŪǥѤΡΣ	using genetic models [7, 2006.01, 2023.01]
G06N   3/123  \	2	2	5B278	G06N   3/123	36	ģΣԥ塼ƥ󥰡Σ	DNA computing [2023.01]
G06N   3/126  \	2	2	5B278	G06N   3/126	893	ʲŪ르ꥺࡢ㡥Ū르ꥺޤϰŪץߥ󥰡Σ	Evolutionary algorithms, e.g. genetic algorithms or genetic programming [2023.01]
G06N   5/00  \	0	0	5B278	G06N   5/00	91	μ١ǥѤ׻֡Σ	Computing arrangements using knowledge-based models [7, 2006.01, 2023.01]
G06N   5/01  \	1	1	5B278	G06N   5/01	46	ưŪõˡҥ塼ꥹƥåʥߥåĥ꡼ʬ޸ˡΣ	Dynamic search techniques; Heuristics; Dynamic trees; Branch-and-bound [2023.01]
G06N   5/02  \	1	1	5B278	G06N   5/02	834	μɽܥɽΣ	Knowledge representation; Symbolic representation [7, 2006.01, 2023.01]
G06N   5/022  \	2	2	5B278	G06N   5/022	1835	μءμΣ	Knowledge engineering; Knowledge acquisition [2023.01]
G06N   5/025  \	3	3	5B278	G06N   5/025	274	ǡε§СΣ	Extracting rules from data [2023.01]
G06N   5/04  \	1	1	5B278	G06N   5/04	3749	ǥΣ	Inference or reasoning models [7, 2006.01, 2023.01]
G06N   5/043  \	2	2	5B278	G06N   5/043	359	ʬѡȥƥࡨ֥åܡɥƥΣ	Distributed expert systems; Blackboards [2023.01]
G06N   5/045  \	2	2	5B278	G06N   5/045	150	ǽʿ͹ǽΣأɡϡǽʿ͹ǽΣ	Explanation of inference; Explainable artificial intelligence [XAI]; Interpretable artificial intelligence [2023.01]
G06N   5/046  \	2	2	5B278	G06N   5/046	218	ץ󥷥ƥΣ	Forward inferencing; Production systems [2023.01]
G06N   5/047  \	3	3	5B278	G06N   5/047	105	ѥޥå󥰥ͥåȥңͥåȥΣ	Pattern matching networks; Rete networks [2023.01]
G06N   5/048  \	2	2	5B278	G06N   5/048	292	եΣ	Fuzzy inferencing [2023.01]
G06N   7/00  \	0	0	5B278	G06N   7/00	245	οŪǥ˴Ť׻֡Σ	Computing arrangements based on specific mathematical models [7, 2006.01, 2023.01]
G06N   7/01  \	1	1	5B278	G06N   7/01	738	ΨŪեǥ롤㡥ΨͥåȥΣ	Probabilistic graphical models, e.g. probabilistic networks [2023.01]
G06N   7/02  \	1	1	5B278	G06N   7/02	728	եѤΡʪŪǥ˴Ťԥ塼ƥǣΣμ١ǥѤԥ塼ƥǣΣˡΣ	using fuzzy logic (computing arrangements based on biological models G06N 3/00; computing arrangements using knowledge-based models G06N 5/00) [7, 2006.01]
G06N   7/02 130 \	2	2	5B278	G06N   7/02	318	եƥΥѥ᡼γؽޤϥ塼˥	learning or tuning of parameter of fuzzy system
G06N   7/02 160 \	2	2	5B278	G06N   7/02	193	եƥΥѥ᡼Ϥ뤿γȯġ	developing tool for inputting  parameter of fuzzy system
G06N   7/04  \	2	2	5B278	G06N   7/04	164	ʪŪʼ¸Σ	Physical realisation [7, 2006.01]
G06N   7/06  \	2	2	5B278	G06N   7/06	2	ѥԥ塼ǤΥߥ졼Σ	Simulation on general purpose computers [7, 2006.01]
G06N   7/08  \	1	1	5B278	G06N   7/08	59	ǥޤƥǥѤΡΣ	using chaos models or non-linear system models [7, 2006.01]
G06N  10/00  \	0	0	5B278	G06N  10/00	644	̻ҥԥ塼ƥ󥰡ʤ̻ϳŪݤ˴ŤΣ	Quantum computing, i.e. information processing based on quantum-mechanical phenomena [2019.01, 2022.01]
G06N  10/20  \	1	1	5B278	G06N  10/20	261	̻ҥԥ塼ƥ󥰥ǥ롤㡥̻Ҳϩޤ̻ҥԥ塼Σ	Models of quantum computing, e.g. quantum circuits or universal quantum computers [2022.01]
G06N  10/40  \	1	1	5B278	G06N  10/40	424	̻ҥӥåȤ㡥̻ҥӥåȤηޤ桤뤿̻ҥץåޤϹǤʪŪʼ¸ޤϥƥΣ	Physical realisations or architectures of quantum processors or components for manipulating qubits, e.g. qubit coupling or qubit control [2022.01]
G06N  10/60  \	1	1	5B278	G06N  10/60	223	̻ҥ르ꥺࡤ㡥̻ҺŬ̻ҥաꥨޤϥޡѴ˴ŤΡΣ	Quantum algorithms, e.g. based on quantum optimisation, or quantum Fourier or Hadamard transforms [2022.01]
G06N  10/70  \	1	1	5B278	G06N  10/70	140	̻ҸФޤɻߡ㡥ɽޤϥޥå־αΣ	Quantum error correction, detection or prevention, e.g. surface codes or magic state distillation [2022.01]
G06N  10/80  \	1	1	5B278	G06N  10/80	89	̻ҥץߥ󥰡㡥̻ҥԥ塼Ǽ¹ԲǽʥץޤϽ뤿Υ󥿡եޤϥեȥȯåȡ̻ҥԥ塼򥷥ߥ졼Ȥޤ̻ҥԥ塼˥뤿Υץåȥեࡤ㡥饦ɥ١̻ҥԥ塼ƥ󥰡Σ	Quantum programming, e.g. interfaces, languages or software-development kits for creating or handling programs capable of running on quantum computers; Platforms for simulating or accessing quantum computers, e.g. cloud-based quantum computing [2022.01]
G06N  20/00  \	0	0	5B278	G06N  20/00	10532	ؽΣ	
G06N  20/00 130 \	1	1	5B278	G06N  20/00	4815	դؽ	supervised learning
G06N  20/00 160 \	1	1	5B278	G06N  20/00	1281	դʤؽ	unsupervised learning
G06N  20/10  \	1	1	5B278	G06N  20/10	374	ͥˡѤΡ㡥ݡȥ٥ޥΣӣ֣͡ϡΣ	using kernel methods, e.g. support vector machines [SVM]
G06N  20/20  \	1	1	5B278	G06N  20/20	386	󥵥֥ؽΣ	Ensemble learning
G06N  99/00  \	0	0	5B278	G06N  99/00	253	Υ֥饹¾Υ롼פʬवʤΣ	Subject matter not provided for in other groups of this subclass [2010.01]
G06N  99/00 170 \	1	1	5B278	G06N  99/00	11	ʬҥԥ塼ʤ̵ʬҤѤΡʬҤѤΣǣΣ	Molecule computers, i.e. using inorganic molecules (using biomolecules G06N3/00 120)
G06N  99/00 180 \	1	1	5B278	G06N  99/00	2660	õ	solution search
