Pattern Recognition and Machine Learning Toolbox
Pattern Recognition and Machine Learning Toolbox
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Cita come
Mo Chen (2026). Pattern Recognition and Machine Learning Toolbox (https://github.com/PRML/PRMLT), GitHub. Recuperato .
Riconoscimenti
Ispirato: Variational Bayesian Linear Regression, Probabilistic Linear Regression, Variational Bayesian Relevance Vector Machine for Sparse Coding, Bayesian Compressive Sensing (sparse coding) and Relevance Vector Machine, Gram-Schmidt orthogonalization, Kalman Filter and Linear Dynamic System, Kernel Learning Toolbox, EM for Mixture of Bernoulli (Unsupervised Naive Bayes) for clustering binary data, Adaboost, Probabilistic PCA and Factor Analysis, Dirichlet Process Gaussian Mixture Model, Log Probability Density Function (PDF), Naive Bayes Classifier, Hidden Markov Model Toolbox (HMM), MLP Neural Network trained by backpropagation, Logistic Regression for Classification, Pairwise Distance Matrix, Kmeans Clustering, Kernel Kmeans, EM Algorithm for Gaussian Mixture Model (EM GMM), Kmedoids, Normalized Mutual Information, Variational Bayesian Inference for Gaussian Mixture Model, Information Theory Toolbox
Informazioni generali
- Versione (93,6 KB)
-
Visualizza la licenza su GitHub
Compatibilità della release di MATLAB
- Compatibile con qualsiasi release
Compatibilità della piattaforma
- Windows
- macOS
- Linux
| Versione | Pubblicato | Note della release | Action |
|---|---|---|---|
| 1.0.0 | update description |
