hyperparameter-optimization

When users starts Serve cluster with a set of options (http options, checkpoint path) and then connects to it with a different set of options, we should either update it, or error out.

From issue #1302, it appears autosklearn is a bit unstable when run many times in the same script, i.e. in a for loop.

for i in range(400):
    automodel = AutoSklearn(full_resources)
    automodel.fit(x, y)

We currently have no test for this and it would be good to see if we can reproduce the same connection refused error.

Motivation

Since lightgbm v3.3.0, train/cv's arguments have been deprecated as described in optuna/optuna#3013. It would be great to replace such deprecated arguments with recommended way by lightgbm.

Description

Replace the deprecated arguments with callback-ish way. The ta

When running TabularPredictor.fit(), I encounter a BrokenPipeError for some reason.
What is causing this?
Could it be due to OOM error?

Fitting model: XGBoost ...
-34.1179 = Validation root_mean_squared_error score
10.58s = Training runtime
0.03s = Validation runtime
Fitting model: NeuralNetMXNet ...
-34.2849 = Validation root_mean_squared_error score
43.63s =

This issue has been coming up when I use,
automl.predict_proba(input)

I am using the requirements.txt in venv. Shouldn't input have feature names?
This message did not used to come up and I don't know why.

Python 3.10 has been released. We should test it. If all the dependencies support it, we should add it to CI.

In issue SimonBlanke/Hyperactive#8 a problem was found, where the memory usage can increase rapidly.

The error is located in the "_init_search"-method from the "Search"-class.

On systems with ~12gb of ram an "out-of-memory"-error will occur when searching in a high dimensional (>20) search space.

If enter_data() is called with the same train_path twice in a row and the data itself hasn't changed, a new Dataset does not need to be created.

We should add a column which stores some kind of hash of the actual data. When a Dataset would be created, if the metadata and data hash are exactly the same as an existing Dataset, nothing should be added to the ModelHub database and the existing

Describe the bug
Code could be more conform to pep8 and so forth.

To Reproduce
https://app.codacy.com/gh/Neuraxio/Neuraxle/issues?&filters=W3siaWQiOiJMYW5ndWFnZSIsInZhbHVlcyI6W119LHsiaWQiOiJDYXRlZ29yeSIsInZhbHVlcyI6WyJDb2RlU3R5bGUiXX0seyJpZCI6IkxldmVsIiwidmFsdWVzIjpbXX0seyJpZCI6IlBhdHRlcm4iLCJ2YWx1ZXMiOltdfSx7ImlkIjoiQXV0aG9yIiwidmFsdWVzIjpbXX1d

Expected behavior
Less code st