Add random_seed to auto_train API to improve repeatability

[amholler]

Add random_seed (set by default to default_random_seed) to the auto_train API to improve repeatability.

This option is passed to the Ray hyperparameter search algorithm, as a seed to the random
generation of hyperparameter sample order, and to the hyperparameter training job, as seed
where possible to data splitting, parameter initialization, and training set shuffling.

Change the default AutoML search_alg from BasicVariantGenerator, which does not currently take a random
seed parameter, to HyperOptSearch, which does take a random seed parameter. Testing across the 5
validation datasets has shown that HyperOptSearch yielded results similar to BasicVariantGenerator, and
with the random seed specified, the results were much less noisy.

[github-actions]

Unit Test Results

       6 files  ±0         6 suites  ±0   2h 46m 49s ⏱️ + 3m 3s
1 216 tests ±0  1 192 ✔️ ±0  24 💤 ±0  0 ❌ ±0 
3 648 runs  ±0  3 576 ✔️ ±0  72 💤 ±0  0 ❌ ±0 

Results for commit 32f5c7c. ± Comparison against base commit 2c31bc0.