autooptimizer 0.7.3

AutoOptimizer is a python package for optimize ML algorithms.

AutoOptimizer provides tools to automatically optimize machine learning model for a dataset with very little user intervention.

It refers to techniques that allow semi-sophisticated machine learning practitioners and non-experts to discover a good predictive model pipeline for their machine learning algorithm task quickly, with very little intervention other than providing a dataset.

#Prerequisites:

jupyterlab(contains all sub packages except mlxtend) or: {sklearn, matplotlib, mlxtend, numpy}

#Usage:

Optimize scikit learn supervised, unsupervised and ensemble learning models using python.

{DBSCAN, KMeans, MeanShift, LogisticRegression, LinearRegression, KNeighborsClassifier, KNeighborsRegressor, RandomForestClassifier, GradientBoostingClassifier, AdaBoostClassifier, SupportVectorClassifier, DecisionTree}

Metrics for Your Regression Model

Clear data by removing outliers

for more information visit: http://genesiscube.ir/index-6.html

#Contact and Contributing: Please share your good ideas with us. Simply letting us know how we can improve the programm to serve you better. Thanks for contributing with the program.

https://github.com/mrb987/autooptimizer [e-mail]