From 2f3ac489619985ae3a1a5b5114bd36ebbeb9a712 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Mario=20Sa=CC=88nger?= <mario.saenger@student.hu-berlin.de>
Date: Mon, 7 May 2018 18:24:50 +0200
Subject: [PATCH] Remove SVM classifier from evaluation
---
code_mario/clef18_task1_base.py | 23 ++++++++++++-----------
1 file changed, 12 insertions(+), 11 deletions(-)
diff --git a/code_mario/clef18_task1_base.py b/code_mario/clef18_task1_base.py
index a16c72a..fa0eff5 100644
--- a/code_mario/clef18_task1_base.py
+++ b/code_mario/clef18_task1_base.py
@@ -83,41 +83,42 @@ class Clef18Task1Base(LoggingMixin):
("SGD", lambda label, input_dim, output_dim, val_data: SGDClassifier(verbose=1, random_state=42)),
("DT", lambda label, input_dim, output_dim, val_data: DecisionTreeClassifier(random_state=42)),
("RF", lambda label, input_dim, output_dim, val_data: RandomForestClassifier(verbose=1, random_state=42)),
- ("LinearSVM", lambda label, input_dim, output_dim, val_data: LinearSVC(max_iter=10000, verbose=1, random_state=42)),
+ #("LinearSVM", lambda label, input_dim, output_dim, val_data: LinearSVC(max_iter=10000, verbose=1, random_state=42)),
("DNN-200", lambda label, input_dim, output_dim, val_data:
self.create_dnn_classifier("dnn-200", label, val_data, input_dim=input_dim, output_dim=output_dim, hidden_layer_sizes=[200],
- batch_normalization=False, dropout_rate=0.0, epochs=10, batch_size=2)),
+ batch_normalization=False, dropout_rate=0.0, epochs=10, batch_size=16)),
+
("DNN-300", lambda label, input_dim, output_dim, val_data:
self.create_dnn_classifier("dnn-300", label, val_data, input_dim=input_dim, output_dim=output_dim, hidden_layer_sizes=[300],
- batch_normalization=False, dropout_rate=0.0, epochs=50, batch_size=2)),
+ batch_normalization=False, dropout_rate=0.0, epochs=50, batch_size=16)),
("DNN-200-BN-DO", lambda label, input_dim, output_dim, val_data:
self.create_dnn_classifier("dnn-200-bn-do", label, val_data, input_dim=input_dim, output_dim=output_dim, hidden_layer_sizes=[200],
- batch_normalization=True, dropout_rate=0.5, epochs=50, batch_size=2)),
+ batch_normalization=True, dropout_rate=0.5, epochs=50, batch_size=16)),
("DNN-300-BN-DO", lambda label, input_dim, output_dim, val_data:
self.create_dnn_classifier("dnn-300-bn-do", label, val_data, input_dim=input_dim, output_dim=output_dim, hidden_layer_sizes=[300],
- batch_normalization=True, dropout_rate=0.5, epochs=50, batch_size=2)),
+ batch_normalization=True, dropout_rate=0.5, epochs=50, batch_size=16)),
("DNN-200-100", lambda label, input_dim, output_dim, val_data:
self.create_dnn_classifier("dnn-200-100", label, val_data, input_dim=input_dim, output_dim=output_dim, hidden_layer_sizes=[200, 100],
- batch_normalization=False, dropout_rate=0.0, epochs=50, batch_size=2)),
+ batch_normalization=False, dropout_rate=0.0, epochs=50, batch_size=16)),
("DNN-200-200", lambda label, input_dim, output_dim, val_data:
self.create_dnn_classifier("dnn-200-200", label, val_data, input_dim=input_dim, output_dim=output_dim, hidden_layer_sizes=[200, 200],
- batch_normalization=False, dropout_rate=0.0, epochs=50, batch_size=2)),
+ batch_normalization=False, dropout_rate=0.0, epochs=50, batch_size=16)),
("DNN-300-200", lambda label, input_dim, output_dim, val_data:
self.create_dnn_classifier("dnn-300-200", label, val_data, input_dim=input_dim, output_dim=output_dim, hidden_layer_sizes=[300, 200],
- batch_normalization=False, dropout_rate=0.0, epochs=50, batch_size=2)),
+ batch_normalization=False, dropout_rate=0.0, epochs=50, batch_size=16)),
("DNN-200-100-BN-DO", lambda label, input_dim, output_dim, val_data:
self.create_dnn_classifier("dnn-200-100-bn-do", label, val_data, input_dim=input_dim, output_dim=output_dim, hidden_layer_sizes=[200, 100],
- batch_normalization=True, dropout_rate=0.5, epochs=50, batch_size=2)),
+ batch_normalization=True, dropout_rate=0.5, epochs=50, batch_size=16)),
("DNN-200-200-BN-DO", lambda label, input_dim, output_dim, val_data:
self.create_dnn_classifier("dnn-200-200-bn-do", label, val_data, input_dim=input_dim, output_dim=output_dim, hidden_layer_sizes=[200, 200],
- batch_normalization=True, dropout_rate=0.5, epochs=50, batch_size=2)),
+ batch_normalization=True, dropout_rate=0.5, epochs=50, batch_size=16)),
("DNN-300-200-BN-DO", lambda label, input_dim, output_dim, val_data:
self.create_dnn_classifier("dnn-300-200-bn-do", label, val_data, input_dim=input_dim, output_dim=output_dim,hidden_layer_sizes=[300, 200],
- batch_normalization=True, dropout_rate=0.5, epochs=50, batch_size=2)),
+ batch_normalization=True, dropout_rate=0.5, epochs=50, batch_size=16)),
('DU1', lambda label, input_dim, output_dim, val_data: DummyClassifier(strategy="stratified")),
('DU2', lambda label, input_dim, output_dim, val_data: DummyClassifier(strategy="most_frequent"))
--
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