baatout

# with X_train, X_test, Y_train, Y_test
from sklearn_pandas import DataFrameMapper
from sklearn2pmml import PMMLPipeline, sklearn2pmml
from sklearn.linear_model import LogisticRegression
from sklearn.preprocessing import FunctionTransformer

def is_adult(x): return x > 18

clf = PMMLPipeline([
    ("mapper", DataFrameMapper([

baatout

# with X_train, X_test, Y_train, Y_test
import dill
from sklearn_pandas import DataFrameMapper
from sklearn.pipeline import Pipeline
from sklearn.linear_model import LogisticRegression
from sklearn.preprocessing import FunctionTransformer

def is_adult(x): return x > 18

clf = Pipeline([

baatout

# run this anywhere and change the pipeline.pk path
import dill
from pandas import read_csv

url = "https://raw.githubusercontent.com/baatout/ml-in-prod/master/pima-indians-diabetes.csv"
features = ['preg', 'plas', 'pres', 'skin', 'test', 'mass', 'pedi', 'age']
label = 'label'
dataframe = read_csv(url, names=features + [label])
X = dataframe[features]
Y = dataframe[label]