How can I use RandomizedLogisticRegression in Scikit-learn?

Question

I just did not understand the documentation for this class. I can put data using it and get evaluations for functions, but is that all this class should do?

I do not see how I can use it to actually perform a regression using a suitable model. The example in the above documentation just creates an instance of the class, so I don’t see how this should help.

There are methods that perform the "transform" operation, but do not mention what kind of transformation it is.

is it possible to use this class to get actual predictions from new test data, and can it be used in cross-checking to compare performance with other methods that I use?

I used the most rated functions in other classifiers, but I'm not sure that more is possible with this classifier.

Update . I found use for fit_transform under the select function in the documentation part:

When the goal is to reduce the dimensionality of data for use with another classifier, they set the conversion method to select a nonzero coefficient

If I don’t get an answer that says I'm wrong, I assume that this classifier does not really make predictions. I will wait before answering my question.

Answer 1

LR , . API scikit-learn:

randomlr = RandomizedLogisticRegression()
X_train = randomlr.fit_transform(X_train)
X_test = randomlr.transform(X_test)

X_train X_test, .