feat: hyperparameter optimization for classical models#843
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Closes #264
Adjusted classical ML-Models to support taking a Choice Parameter
New Features for Classifiers and Regressors:
combined Linear,Lasso,Ridge and ElasticNetRegressor into ElasticNetRegressor
changed property methods and parameter types
added fit_by_exhaustive_search(), to fit a model with all combinations of given Choices
added Errors for using the wrong fit method (fit with or fit_by_exhaustive_search without Choice Parameter)
added Enums ClassifierMetric and RegressorMetric, which are passed to fit_by_exhaustive_search to determine the optimization metric
added cross validation in fit_by_exhaustive_search
added multiprocessing in fit_by_exhaustive_search
added tests for all methods and classes