Added one copyright and license notice in randomforest_all as example

Author: Pascual Martinez-Gomez

en/emnlp2017exp.sh

@@ -40,16 +40,18 @@ fi
 #    sub(/\.$/,"",$3);
 #    premise=$2;
 #    conclusion=$3;
-#    if($4 == "CONTRADICTION"){
+#    score=$4;
+#    if($5 == "CONTRADICTION"){
 #      judgement="no";
-#    } else if ($4 == "ENTAILMENT") {
+#    } else if ($5 == "ENTAILMENT") {
 #      judgement="yes";
-#    } else if ($4 == "NEUTRAL") {
+#    } else if ($5 == "NEUTRAL") {
 #      judgement="unknown";
 #    }
 #    set=$12;
-#    printf "%s.\n%s.\n", premise, conclusion > "en_plain/sick_"tolower(set)"_"pair_id".txt";
-#    printf "%s\n", judgement > "en_plain/sick_"tolower(set)"_"pair_id".answer";
+#    printf "%s.\n%s.\n", premise, conclusion > "plain/sick_"tolower(set)"_"pair_id".txt";
+#    printf "%s\n", judgement > "plain/sick_"tolower(set)"_"pair_id".answer";
+#    printf "%s\n", score > "plain2/sick_"tolower(set)"_"pair_id".answer";
 #   }'
 
 # Create files that list all filenames of training, testing and trial.

scripts/randomforest_all.py

@@ -1,4 +1,20 @@
 #!/usr/bin/python
+# -*- coding: utf-8 -*-
+#
+#  Copyright 2017 Hitomi Yanaka
+#
+#  Licensed 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.
+
 
 import os
 import numpy as np
@@ -31,7 +47,7 @@ def regression(X_train, y_train, X_test, y_test):
     parameters = {
         'n_estimators'      : [10, 50, 100, 200, 300],
         'random_state'      : [0],
-        'n_jobs'            : [1],
+        'n_jobs'            : [200],
         'max_features'      : ['auto', 'log2', 'sqrt', None],
         'criterion'         : ['mse'],
         'max_depth'         : [3, 5, 10, 20, 30, 40, 50, 100]