#!/usr/bin/env python
# coding: utf-8

# In[1]:


import h2o
from h2o.estimators.deeplearning import H2ODeepLearningEstimator


# In[2]:


h2o.init()


# In[3]:


from h2o.utils.shared_utils import _locate # private function. used to find files within h2o git project directory.

prostate = h2o.upload_file(path=_locate("smalldata/logreg/prostate.csv"))
prostate.describe()


# In[4]:


prostate["CAPSULE"] = prostate["CAPSULE"].asfactor()
model = H2ODeepLearningEstimator(activation = "Tanh", hidden = [10, 10, 10], epochs = 10000)
model.train(x = list(set(prostate.columns) - set(["ID","CAPSULE"])), y ="CAPSULE", training_frame = prostate)
model.show()


# In[5]:


predictions = model.predict(prostate)
predictions.show()


# In[6]:


performance = model.model_performance(prostate)
performance.show()