"""
Script that trains Sklearn multitask models on MUV dataset.
"""
from __future__ import print_function
from __future__ import division
from __future__ import unicode_literals
import os
import shutil
import numpy as np
import deepchem as dc
from deepchem.molnet import load_muv
from sklearn.ensemble import RandomForestClassifier
np.random.seed(123)
# Load MUV dataset
muv_tasks, muv_datasets, transformers = load_muv()
(train_dataset, valid_dataset, test_dataset) = muv_datasets
# Fit models
metric = dc.metrics.Metric(
dc.metrics.roc_auc_score, np.mean, mode="classification")
def model_builder(model_dir):
sklearn_model = RandomForestClassifier(
class_weight="balanced", n_estimators=500)
return dc.models.SklearnModel(sklearn_model, model_dir)
model = dc.models.SingletaskToMultitask(muv_tasks, model_builder)
# Fit trained model
model.fit(train_dataset)
model.save()
# Evaluate train/test scores
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)
