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author | Omede Firouz <ofirouz@palantir.com> | 2015-05-03 11:42:02 -0700 |
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committer | Xiangrui Meng <meng@databricks.com> | 2015-05-03 11:42:02 -0700 |
commit | f4af92550cb90e47a12d4625fa615dd2b1587d42 (patch) | |
tree | 59b1aaff420319f43363f5697118887057a7ac05 /python/pyspark/ml | |
parent | 49549d5a1a867c3ba25f5e4aec351d4102444bc0 (diff) | |
download | spark-f4af92550cb90e47a12d4625fa615dd2b1587d42.tar.gz spark-f4af92550cb90e47a12d4625fa615dd2b1587d42.tar.bz2 spark-f4af92550cb90e47a12d4625fa615dd2b1587d42.zip |
[SPARK-7022] [PYSPARK] [ML] Add ML.Tuning.ParamGridBuilder to PySpark
Author: Omede Firouz <ofirouz@palantir.com>
Author: Omede <omedefirouz@gmail.com>
Closes #5601 from oefirouz/paramgrid and squashes the following commits:
c9e2481 [Omede Firouz] Make test a doctest
9a8ce22 [Omede] Fix linter issues
8b8a6d2 [Omede Firouz] [SPARK-7022][PySpark][ML] Add ML.Tuning.ParamGridBuilder to PySpark
Diffstat (limited to 'python/pyspark/ml')
-rw-r--r-- | python/pyspark/ml/tuning.py | 94 |
1 files changed, 94 insertions, 0 deletions
diff --git a/python/pyspark/ml/tuning.py b/python/pyspark/ml/tuning.py new file mode 100644 index 0000000000..a383bd0c0d --- /dev/null +++ b/python/pyspark/ml/tuning.py @@ -0,0 +1,94 @@ +# +# 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. +# + +__all__ = ['ParamGridBuilder'] + + +class ParamGridBuilder(object): + """ + Builder for a param grid used in grid search-based model selection. + + >>> from classification import LogisticRegression + >>> lr = LogisticRegression() + >>> output = ParamGridBuilder().baseOn({lr.labelCol: 'l'}) \ + .baseOn([lr.predictionCol, 'p']) \ + .addGrid(lr.regParam, [1.0, 2.0, 3.0]) \ + .addGrid(lr.maxIter, [1, 5]) \ + .addGrid(lr.featuresCol, ['f']) \ + .build() + >>> expected = [ \ +{lr.regParam: 1.0, lr.featuresCol: 'f', lr.maxIter: 1, lr.labelCol: 'l', lr.predictionCol: 'p'}, \ +{lr.regParam: 2.0, lr.featuresCol: 'f', lr.maxIter: 1, lr.labelCol: 'l', lr.predictionCol: 'p'}, \ +{lr.regParam: 3.0, lr.featuresCol: 'f', lr.maxIter: 1, lr.labelCol: 'l', lr.predictionCol: 'p'}, \ +{lr.regParam: 1.0, lr.featuresCol: 'f', lr.maxIter: 5, lr.labelCol: 'l', lr.predictionCol: 'p'}, \ +{lr.regParam: 2.0, lr.featuresCol: 'f', lr.maxIter: 5, lr.labelCol: 'l', lr.predictionCol: 'p'}, \ +{lr.regParam: 3.0, lr.featuresCol: 'f', lr.maxIter: 5, lr.labelCol: 'l', lr.predictionCol: 'p'}] + >>> fail_count = 0 + >>> for e in expected: + ... if e not in output: + ... fail_count += 1 + >>> if len(expected) != len(output): + ... fail_count += 1 + >>> fail_count + 0 + """ + + def __init__(self): + self._param_grid = {} + + def addGrid(self, param, values): + """ + Sets the given parameters in this grid to fixed values. + """ + self._param_grid[param] = values + + return self + + def baseOn(self, *args): + """ + Sets the given parameters in this grid to fixed values. + Accepts either a parameter dictionary or a list of (parameter, value) pairs. + """ + if isinstance(args[0], dict): + self.baseOn(*args[0].items()) + else: + for (param, value) in args: + self.addGrid(param, [value]) + + return self + + def build(self): + """ + Builds and returns all combinations of parameters specified + by the param grid. + """ + param_maps = [{}] + for (param, values) in self._param_grid.items(): + new_param_maps = [] + for value in values: + for old_map in param_maps: + copied_map = old_map.copy() + copied_map[param] = value + new_param_maps.append(copied_map) + param_maps = new_param_maps + + return param_maps + + +if __name__ == "__main__": + import doctest + doctest.testmod() |