Unsupervised learning
Unsupervised learning is a type of algorithm that learns patterns from untagged data. The hope is that through mimicry, which is an important mode of learning in people, the machine is forced to build a concise representation of its world and then generate imaginative content from it.
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- enUnsupervised learning is a type of algorithm that learns patterns from untagged data. The hope is that through mimicry, which is an important mode of learning in people, the machine is forced to build a concise representation of its world and then generate imaginative content from it.
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- Has abstract
- enUnsupervised learning is a type of algorithm that learns patterns from untagged data. The hope is that through mimicry, which is an important mode of learning in people, the machine is forced to build a concise representation of its world and then generate imaginative content from it. In contrast to supervised learning where data is tagged by an expert, e.g. tagged as a "ball" or "fish", unsupervised methods exhibit self-organization that captures patterns as probability densities or a combination of neural feature preferences encoded in the machine's weights and activations. The other levels in the supervision spectrum are reinforcement learning where the machine is given only a numerical performance score as guidance, and semi-supervised learning where a small portion of the data is tagged.
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- Machine
- Is primary topic of
- Unsupervised learning
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- enUnsupervised learning
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- link.springer.com/chapter/10.1007/978-0-387-84858-7_14
- archive.org/details/springer_10.1007-b100712
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- Adaptive resonance theory
- Anomaly detection
- A priori probability
- Artificial neural network
- Automated machine learning
- Automatic target recognition
- Backpropagation
- Blind signal separation
- Boltzmann Machine
- Category:Machine learning
- Category:Unsupervised learning
- Cluster analysis
- Conditional probability distribution
- Covariance matrix
- Data clustering
- DBSCAN
- Deep Belief Network
- Density estimation
- Donald Hebb
- Expectation–maximization algorithm
- File:Autoencoder schema.png
- File:Boltzmannexamplev1.png
- File:Helmholtz Machine.png
- File:Hopfield-net-vector.svg
- File:Restricted Boltzmann machine.svg
- File:Stacked-boltzmann.png
- File:Task-guidance.png
- File:VAE blocks.png
- Generative topographic map
- Geoffrey Hinton
- Hebbian learning
- Helmholtz machine
- Hierarchical clustering
- Hopfield Network
- Independent component analysis
- Isolation Forest
- K-means
- Labeled data
- Latent variable model
- Local Outlier Factor
- Machine learning
- Mean
- Meta-learning (computer science)
- Method of moments (statistics)
- MIT Press
- Mixture models
- Multivariate analysis
- Neural network
- Non-negative matrix factorization
- OPTICS algorithm
- Pattern recognition
- Principal component analysis
- Radial basis function network
- Reinforcement learning
- Self-organizing map
- Semi-supervised learning
- Singular value decomposition
- Spike-timing-dependent plasticity
- Statistics
- Supervised learning
- Tensors
- Terry Sejnowski
- Topic modeling
- Variational autoencoder
- Variational Bayesian methods
- Venn diagram
- Weak supervision
- SameAs
- 4580265-8
- Apprendimento non supervisionato
- Apprentissage non supervisé
- Aprendizaje no supervisado
- Aprenentatge no supervisat
- Cuib
- Gözetimsiz öğrenme
- Hindi pinapatnubayang pagkatuto
- Học không có giám sát
- Juhendamata masinõpe
- m.01hylt
- Ohjaamaton oppiminen
- Pemelajaran tak terarah
- Q1152135
- Učení bez učitele
- Uczenie nienadzorowane
- Unüberwachtes Lernen
- Μη επιβλεπόμενη μάθηση
- Навчання без учителя
- Обучение без учителя
- למידה בלתי מונחית
- تعلم غير مراقب
- فێربوونی چاودێرینەکراو
- یادگیری خودران (خودسازمانده)
- การเรียนรู้แบบไม่มีผู้สอน
- 教師なし学習
- 無監督學習
- 비지도 학습
- SeeAlso
- Supervised learning
- Subject
- Category:Machine learning
- Category:Unsupervised learning
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- Unsupervised learning?oldid=1122854118&ns=0
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- Wikipage page ID
- 233497
- Wikipage revision ID
- 1122854118
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