sample.py

from yhat import Yhat, BaseModel
from sklearn import datasets
from sklearn.svm import SVC

class IrisModel(yhat.BaseModel):
    def transform(self, data):
        data = [
        data['SepalLength'],
        data['SepalWidth'] / 2.0,
        data['PetalLength'],
        data['PetalWidth']^2
        ]

        return data

    def predict(self, transformedData):
        return self.clf.predict(transformedData)

clf = SVC().fit(X_transformed, y)
yhat.upload(name="irisClassifier", model=IrisModel(clf=clf))