v2.0.0

API-change to improve usage. Class accepts training data. "search"-method accepts search_config and other optimization-run specific arguments like n_iter, n_jobs, optimizer.

v1.1.1

• small api-change
• extend progress bar information
• re-enable multiprocessing for new api

v1.0.0

• new API that creates model by function and search space by dict
• enables more flexible usage (e.g. free use of framework, ensembles, nn-structure)
• 100% test coverage

v0.4.2

• performance fixes for bayesian optimization and parallel tempering
• better default parameter for most optimizers
• better implementation for metrics
• add support for catboost
• integration of meta-learn code into hyperactive
• cleanup to avoid similar code

v0.4.1.2

• k-fold-cross validation works with keras models
• a cv of < 1 trains the model on a fraction of the training data and tests on the rest
• better testing and code-coverage
• fix of score and predict method

v0.4.0

• improvement of optimizer class structure
• lower memory usage
• add testing of optimization process
• a lot of clean up und several bug fixes (mostly parallel tempering)

v0.3.5

• improved scatter initialization
• remove small bug in random seed
• add basic test

v0.3.4

• add tabu search
• add parallel tempering
• add bayesian optimization

v0.3.3

• add stochastic hill climbing
• random restart hill climbing
• stochastic tunneling

v0.3.2

• set memory to true
• add hill climbing algorithm
• add random annealing algorithm