AutoOptimizer package provides tools for automatically optimizing machine learning models.
It uses Exhaustive Search Mechanism with Hyperparameter Tuning for optimizing machine learning models. It also provides evaluation metrics for regression models, and ability to delete outliers with several methods.
#Prerequisites:
{ sklearn - numpy - pandas }
#Install package:
pip install autooptimzer
#Install package in jupyter notebook:
1- open anaconda prompt (It is recommended open as administrator)
2- pip install autooptimzer
#Usage:
Optimize machine learning models using python.
Clustering: DBSCAN, KMeans, MeanShift, Mini Batch K-Means
Supervised: KNeighborsClassifier, KNeighborsRegressor, DecisionTreeClassifier, DecisionTreeRegressor, SupportVectorClassifier, SupportVectorRegressor, LogisticRegression, LinearRegression
Ensemble: RandomForestClassifier, RandomForestRegressor, GradientBoostingClassifier, GradientBoostingRegressor, AdaBoostClassifier, AdaBoostRegressor, BaggingClassifier, BaggingRegressor, ExtraTreesClassifier
Metrics for regression models.
Clear data by removing outliers.
Download Document: https://genesiscube.ir/wp-content/uploads/2023/03/Auto-Optimizer-document-0.8.9.pdf
For more information visit: https://genesiscube.ir/autooptimizer/
#Contact and Contributing:
Please share your good ideas with us. Thanks for contributing with the program.
1 maintainer
Metadata
1 maintainer
Release files for autooptimizer 0.8.9
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| autooptimizer-0.8.9.tar.gz | 9.5 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| autooptimizer-0.8.9-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 27.9 kB
Release files / autooptimizer-0.8.9.tar.gz
| Download URL | autooptimizer-0.8.9.tar.gz |
|---|---|
| Size | 9.5 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.9.7
|
Release files / autooptimizer-0.8.9-py3-none-any.whl
| Download URL | autooptimizer-0.8.9-py3-none-any.whl |
|---|---|
| Size | 18.4 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.9.7
|
