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prenigma-automl

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2.1.2 prenigma_automl-2.1.2-py3-none-any.whl

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Project: prenigma-automl
Version: 2.1.2
Filename: prenigma_automl-2.1.2-py3-none-any.whl
Download: [link]
Size: 252464
MD5: 1860b7b86db7471069d195427182db79
SHA256: 0368e9f88b4e251a21790a1dc28a8b157b7dce7d9dc1a093c69306d6fe4aeff3
Uploaded: 2020-09-03 21:54:33 +0000

dist-info

METADATA · WHEEL · RECORD · top_level.txt

METADATA

Metadata-Version: 2.1
Name: prenigma-automl
Version: 2.1.2
Summary: prenigma_automl - An open source, low-code machine learning library.
Author: Prenigma
Author-Email: hello[at]predapp.com
Home-Page: https://github.com/prenigma-auto-ml/prenigma_automl
License: MIT
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Requires-Dist: pandas
Requires-Dist: numpy (>=1.17)
Requires-Dist: seaborn
Requires-Dist: matplotlib
Requires-Dist: IPython
Requires-Dist: joblib
Requires-Dist: scikit-learn (>=0.23)
Requires-Dist: ipywidgets
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Requires-Dist: xgboost (>=0.90)
Requires-Dist: lightgbm (>=2.3.1)
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Requires-Dist: wordcloud
Requires-Dist: textblob
Requires-Dist: cufflinks (>=0.17.0)
Requires-Dist: umap-learn
Requires-Dist: pyLDAvis
Requires-Dist: gensim
Requires-Dist: spacy
Requires-Dist: nltk
Requires-Dist: mlxtend
Requires-Dist: pyod
Requires-Dist: catboost (>=0.23.2)
Requires-Dist: pandas-profiling (>=2.8.0)
Requires-Dist: kmodes (>=0.10.1)
Requires-Dist: datefinder (>=0.7.0)
Requires-Dist: mlflow
Requires-Dist: imbalanced-learn (>=0.6.2)
Description-Content-Type: text/markdown
[Description omitted; length: 6406 characters]

WHEEL

Wheel-Version: 1.0
Generator: bdist_wheel (0.35.1)
Root-Is-Purelib: true
Tag: py3-none-any

RECORD

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prenigma_automl/anomaly.py sha256=huCoyr5FV6oZ_X14wt_k05WnQP4KMhdawlV3ZPep-3Y 159327
prenigma_automl/arules.py sha256=NBIrreVg7aEPNzTNv6vjWongOnNrGKJQjCxaf1tow5w 10447
prenigma_automl/classification.py sha256=OK7_aXUXZ4hQXVpsJFmPjBFvbw24HqxzDYM9cWeFqLc 414235
prenigma_automl/clustering.py sha256=QkK9zDoV91ZNUodYzVgjpg3qMOux6FD_cCtFmlEVUxw 166202
prenigma_automl/datasets.py sha256=OOEbOLm1wNQxIiKrsIS5XDZIwEJKYemNV4ksBHc9T2A 2244
prenigma_automl/nlp.py sha256=1nkWNWZx2Ek83nl5VpotSpTbPPiAZClUpoKu0gcrKFQ 125520
prenigma_automl/preprocess.py sha256=H-VBD4jWOnPT7rKA6qi_aER8pDb333RqYjjMFk6UnS8 131712
prenigma_automl/regression.py sha256=NunR8WYfWImECjr01l6yzeIxGNuOHIAHTYEdAR2bhc0 349668
prenigma_automl/utils.py sha256=1JykVS8OfeAEmmHzdR9OiZMzZd9ygQ1m9K6m_64Uyf4 3210
prenigma_automl-2.1.2.dist-info/LICENSE sha256=lfiYv27XS1b2dBZqq5IxH2veoc9oueLwajAIQw-_jZE 1102
prenigma_automl-2.1.2.dist-info/METADATA sha256=hbQiZN4HpONR9LtnsUkW0-gJTIZTm8pKNhrWswG3ZiQ 7724
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prenigma_automl-2.1.2.dist-info/top_level.txt sha256=CrJFXgT0TEPA2BAdvCYMY1Raz5i7z4yZ2GtqDCzlQIE 16
prenigma_automl-2.1.2.dist-info/RECORD — —

top_level.txt

prenigma_automl