#!/usr/bin/env python2
# -*- coding: utf-8 -*-
"""
Created on Sun Jul 23 15:04:19 2017
@author: zqwu
"""
from __future__ import print_function
from __future__ import division
from __future__ import unicode_literals
from sklearn.kernel_ridge import KernelRidge
import numpy as np
import deepchem as dc
import tempfile
# Only for debug!
np.random.seed(123)
# Load Delaney dataset
n_features = 1024
delaney_tasks, delaney_datasets, transformers = dc.molnet.load_delaney()
train_dataset, valid_dataset, test_dataset = delaney_datasets
metric = dc.metrics.Metric(dc.metrics.pearson_r2_score, np.mean)
def model_builder(model_dir):
sklearn_model = KernelRidge(kernel="rbf", alpha=1e-3, gamma=0.05)
return dc.models.SklearnModel(sklearn_model, model_dir)
model_dir = tempfile.mkdtemp()
model = dc.models.SingletaskToMultitask(delaney_tasks, model_builder, model_dir)
model.fit(train_dataset)
model.save()
print("Evaluating model")
train_scores = model.evaluate(train_dataset, [metric], transformers)
valid_scores = model.evaluate(valid_dataset, [metric], transformers)
print("Train scores")
print(train_scores)
print("Validation scores")
print(valid_scores)
