1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
|
#
# Licensed to the Apache Software Foundation (ASF) under one or more
# contributor license agreements. See the NOTICE file distributed with
# this work for additional information regarding copyright ownership.
# The ASF licenses this file to You under the Apache License, Version 2.0
# (the "License"); you may not use this file except in compliance with
# the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
from __future__ import print_function
from pyspark import SparkContext
from pyspark.sql import SQLContext
# $example on$
from pyspark.ml.regression import AFTSurvivalRegression
from pyspark.mllib.linalg import Vectors
# $example off$
if __name__ == "__main__":
sc = SparkContext(appName="AFTSurvivalRegressionExample")
sqlContext = SQLContext(sc)
# $example on$
training = sqlContext.createDataFrame([
(1.218, 1.0, Vectors.dense(1.560, -0.605)),
(2.949, 0.0, Vectors.dense(0.346, 2.158)),
(3.627, 0.0, Vectors.dense(1.380, 0.231)),
(0.273, 1.0, Vectors.dense(0.520, 1.151)),
(4.199, 0.0, Vectors.dense(0.795, -0.226))], ["label", "censor", "features"])
quantileProbabilities = [0.3, 0.6]
aft = AFTSurvivalRegression(quantileProbabilities=quantileProbabilities,
quantilesCol="quantiles")
model = aft.fit(training)
# Print the coefficients, intercept and scale parameter for AFT survival regression
print("Coefficients: " + str(model.coefficients))
print("Intercept: " + str(model.intercept))
print("Scale: " + str(model.scale))
model.transform(training).show(truncate=False)
# $example off$
sc.stop()
|
