文件名称：Python-pomegranate是Python中快速灵活且易于使用的概率建模工具包
文件大小：1.23MB
文件格式：ZIP
更新时间：2022-08-29 10:42:14
Python开发-机器学习
pomegranate是Python中快速，灵活且易于使用的概率建模工具包
【文件预览】：
jmschrei-pomegranate-0b16172
----MANIFEST.in(35B)
----benchmarks()
--------pomegranate_vs_sklearn_gmm.ipynb(531KB)
--------benchmark_distributions.py(5KB)
--------pomegranate_vs_hmmlearn.ipynb(189KB)
--------pomegranate_vs_sklearn_naive_bayes.ipynb(523KB)
--------benchmark_hmm.py(6KB)
----tutorials()
--------Tutorial_2_General_Mixture_Models.ipynb(31KB)
--------Tutorial_6_Markov_Chain.ipynb(7KB)
--------Tutorial_3_Hidden_Markov_Models.ipynb(69KB)
--------Tutorial_4_Bayesian_Networks.ipynb(16KB)
--------README.md(481B)
--------Tutorial_5_Naive_Bayes.ipynb(66KB)
--------Tutorial_1_Distributions.ipynb(84KB)
----examples()
--------fsm_example.ipynb(5KB)
--------distributions_conditionalupdate.ipynb(5KB)
--------hmm_infinite.ipynb(12KB)
--------bayesnet_monty_hall_train.ipynb(8KB)
--------bayesnet_huge_monty_hall.ipynb(12KB)
--------naivebayes_multivariate_male_female.ipynb(5KB)
--------hmm_fsm_comparison.ipynb(10KB)
--------fsm_vending.ipynb(6KB)
--------hmm_tied_states.ipynb(20KB)
--------bayesnet_monty_hall_classic.ipynb(14KB)
--------naivebayes_bayes_net.ipynb(9KB)
--------naivebayes_rain_fog.ipynb(16KB)
--------naivebayes_hmm_cheating_coin_toss.ipynb(83KB)
--------fsm_test.ipynb(8KB)
--------bayesnet_asia.ipynb(10KB)
--------hmm_rainy_sunny.ipynb(6KB)
--------distributions_test_table.ipynb(6KB)
--------hmm_example.ipynb(9KB)
--------naivebayes_simple_male_female.ipynb(21KB)
----.travis.yml(1018B)
----mkdocs.yml(489B)
----LICENSE(1KB)
----setup.py(1KB)
----README.md(22KB)
----CHANGES.txt(3KB)
----docs()
--------source()
--------index.md~(20KB)
--------Makefile(7KB)
----MANIFEST(608B)
----tests()
--------test_naive_bayes.py(17KB)
--------test_distributions.py(19KB)
--------test_markov_chain.py(19KB)
--------test_gmm.py(5KB)
--------__init__.py(0B)
--------test_titanic.py(4KB)
--------test_huge_monty_hall.py(7KB)
--------test_fsm.py(2KB)
--------test_profile_hmm.py(17KB)
--------test_bayes_net.py(5KB)
--------test_hmm_training.py(17KB)
----.gitignore(29B)
----pomegranate()
--------NaiveBayes.pyx(10KB)
--------utils.pyx(4KB)
--------utils.pxd(218B)
--------__init__.py(1KB)
--------BayesianNetwork.pyx(12KB)
--------hmm.pyx(104KB)
--------gmm.pyx(22KB)
--------MarkovChain.pyx(6KB)
--------fsm.pyx(9KB)
--------FactorGraph.pyx(12KB)
--------distributions.pxd(3KB)
--------base.pxd(382B)
--------distributions.pyx(80KB)
--------base.pyx(9KB)