There are a lot of changes in scikit-learn 1.2.0 where it supports pandas output for all of the transformers but how can I use it in a custom transformer? In [1]: Here is my custom transformer whic...

I've fit a Pipeline object with RandomizedSearchCV pipe_sgd = Pipeline([('scl', StandardScaler()), ('clf', SGDClassifier(n_jobs=-1))]) param_dist_sgd = {'clf__loss': ['log'], 'clf__penalty': [N...

I am implementing an example from the O'Reilly book "Introduction to Machine Learning with Python", using Python 2.7 and sklearn 0.16. The code I am using: pipe = make_pipeline(TfidfVectorizer(),...

I have text as shown : list1 = ["My name is xyz", "My name is pqr", "I work in abc"] The above will be training set for clustering text using kmeans. list2 = ["My name is xyz", "I work in abc"...

I wonder if we can set up an "optional" step in sklearn.pipeline. For example, for a classification problem, I may want to try an ExtraTreesClassifier with AND without a PCA transformation ahead of...

My goal is to use one model to select the most important variables and another model to use those variables to make predictions. In the example below I am using two instances of RandomForestClassif...