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prenigmaautoml

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2.1.2 prenigmaautoml-2.1.2-py3-none-any.whl

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Project: prenigmaautoml
Version: 2.1.2
Filename: prenigmaautoml-2.1.2-py3-none-any.whl
Download: [link]
Size: 252457
MD5: 1675f2f380f3910583d4437f158cb6c8
SHA256: d23527b83a8f3d3d124fce56feca80e27e600d1b93f91452114d4e497b107056
Uploaded: 2020-09-04 15:55:15 +0000

dist-info

METADATA · WHEEL · RECORD · top_level.txt

METADATA

Metadata-Version: 2.1
Name: prenigmaautoml
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
Requires-Dist: yellowbrick (>=1.0.1)
Requires-Dist: xgboost (>=0.90)
Requires-Dist: lightgbm (>=2.3.1)
Requires-Dist: plotly (>=4.4.1)
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

Path Digest Size
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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
prenigmaautoml-2.1.2.dist-info/LICENSE sha256=lfiYv27XS1b2dBZqq5IxH2veoc9oueLwajAIQw-_jZE 1102
prenigmaautoml-2.1.2.dist-info/METADATA sha256=SXtTBJ7aOytOEpGnxTuSO30pZI_5TGhfVKD5_e_-uMs 7723
prenigmaautoml-2.1.2.dist-info/WHEEL sha256=EVRjI69F5qVjm_YgqcTXPnTAv3BfSUr0WVAHuSP3Xoo 92
prenigmaautoml-2.1.2.dist-info/top_level.txt sha256=CrJFXgT0TEPA2BAdvCYMY1Raz5i7z4yZ2GtqDCzlQIE 16
prenigmaautoml-2.1.2.dist-info/RECORD — —

top_level.txt

prenigma_automl