Problem with pipeline.fit() about mlblocks

[csala]

Thanks for your feedback @NajatAbd

I have tried reproducing the error running python 3.6 in Linux and everything works as expected:

In [1]: from sklearn.datasets import load_iris
   ...: from sklearn.model_selection import train_test_split
   ...: from mlblocks import MLPipeline
   ...: import pandas as pd
   ...: 
   ...: 

In [2]: primitives = [
   ...:      'sklearn.preprocessing.StandardScaler',
   ...:     'sklearn.ensemble.RandomForestClassifier'
   ...:  ]
   ...: pipeline = MLPipeline(primitives)
   ...:  

In [3]: iris = load_iris()
   ...: 
   ...: X_train, X_test, y_train, y_test = train_test_split(iris.data, iris.target,  test_size=0.2,random_state=7)
   ...: 
   ...: 

In [4]: pipeline.fit(X_train, y_train)
   ...: 

So, I suspect that this is either a Mac OSX issue or a version mismatch.

What version of scikit-learn are you using? I'm on 0.19.2:

$ pip freeze | grep scikit-learn
scikit-learn==0.19.2

[NajatAbd]

Thank you! The code is now working just fine..