From bb2cdc963686e0b68dc6f1160cc00920adad3541 Mon Sep 17 00:00:00 2001
From: Alex <croix.alexandre@gmail.com>
Date: Fri, 13 Sep 2019 11:17:35 +0200
Subject: [PATCH] Modification MainDL4J for parametric study
---
java-wowa-training.iml | 4 +-
.../be/cylab/java/wowa/training/MainDL4J.java | 70 +++++++++++++------
2 files changed, 50 insertions(+), 24 deletions(-)
diff --git a/java-wowa-training.iml b/java-wowa-training.iml
index 08c09f6..e65012b 100644
--- a/java-wowa-training.iml
+++ b/java-wowa-training.iml
@@ -42,13 +42,15 @@
<orderEntry type="library" name="Maven: info.debatty:java-aggregation:0.5" level="project" />
<orderEntry type="library" name="Maven: com.owlike:genson:1.6" level="project" />
<orderEntry type="library" name="Maven: org.apache.commons:commons-lang3:3.8.1" level="project" />
- <orderEntry type="library" name="Maven: be.cylab:java-roc:0.0.3" level="project" />
+ <orderEntry type="library" name="Maven: be.cylab:java-roc:0.0.4" level="project" />
<orderEntry type="library" name="Maven: com.opencsv:opencsv:4.5" level="project" />
<orderEntry type="library" name="Maven: org.apache.commons:commons-text:1.3" level="project" />
<orderEntry type="library" name="Maven: commons-beanutils:commons-beanutils:1.9.3" level="project" />
<orderEntry type="library" name="Maven: commons-logging:commons-logging:1.2" level="project" />
<orderEntry type="library" name="Maven: commons-collections:commons-collections:3.2.2" level="project" />
<orderEntry type="library" name="Maven: org.apache.commons:commons-collections4:4.2" level="project" />
+ <orderEntry type="library" name="Maven: org.knowm.xchart:xchart:3.5.4" level="project" />
+ <orderEntry type="library" name="Maven: de.erichseifert.vectorgraphics2d:VectorGraphics2D:0.13" level="project" />
<orderEntry type="library" name="Maven: org.datavec:datavec-api:0.9.1" level="project" />
<orderEntry type="library" name="Maven: org.apache.commons:commons-compress:1.8.1" level="project" />
<orderEntry type="library" name="Maven: org.apache.commons:commons-math3:3.3" level="project" />
diff --git a/src/main/java/be/cylab/java/wowa/training/MainDL4J.java b/src/main/java/be/cylab/java/wowa/training/MainDL4J.java
index cf2f3ec..20f2bd6 100644
--- a/src/main/java/be/cylab/java/wowa/training/MainDL4J.java
+++ b/src/main/java/be/cylab/java/wowa/training/MainDL4J.java
@@ -4,6 +4,12 @@ import org.deeplearning4j.nn.api.OptimizationAlgorithm;
import org.deeplearning4j.nn.multilayer.MultiLayerNetwork;
import org.nd4j.linalg.activations.Activation;
+import java.io.FileOutputStream;
+import java.io.IOException;
+import java.io.OutputStreamWriter;
+import java.nio.charset.StandardCharsets;
+import java.util.HashMap;
+
/**
* Class for learn in neuronal network.
*/
@@ -21,20 +27,24 @@ public final class MainDL4J {
* @param args
*/
public static void main(final String[] args) {
-
- //String file_name = args[0];
- double learning_rate = Double.parseDouble(args[1]);
+ int begin_neuron_number = Integer.parseInt(args[0]);
+ int neuron_number_end = Integer.parseInt(args[1]);
+ String data_file = args[5];
+ String expected_file = args[6];
+ double learning_rate = Double.parseDouble(args[2]);
OptimizationAlgorithm optimization_algorithm;
Activation activation_function;
+ int fold_number = 10;
+ int increase_ratio = 10;
- if (args[2].matches("CONJUGATE_GRADIENT")) {
+ if (args[3].matches("CONJUGATE_GRADIENT")) {
optimization_algorithm = OptimizationAlgorithm.CONJUGATE_GRADIENT;
- } else if (args[2].matches("LBFGS")) {
+ } else if (args[3].matches("LBFGS")) {
optimization_algorithm = OptimizationAlgorithm.LBFGS;
- } else if (args[2].matches("LINE_GRADIENT_DESCENT")) {
+ } else if (args[3].matches("LINE_GRADIENT_DESCENT")) {
optimization_algorithm
= OptimizationAlgorithm.LINE_GRADIENT_DESCENT;
- } else if (args[2].matches("STOCHASTIC_GRADIENT_DESCENT")) {
+ } else if (args[3].matches("STOCHASTIC_GRADIENT_DESCENT")) {
optimization_algorithm
= OptimizationAlgorithm.STOCHASTIC_GRADIENT_DESCENT;
} else {
@@ -42,32 +52,46 @@ public final class MainDL4J {
"Not correct optimization algorithm");
}
- if (args[3].matches("RELU")) {
+ if (args[4].matches("RELU")) {
activation_function = Activation.RELU;
- } else if (args[3].matches("SIGMOID")) {
+ } else if (args[4].matches("SIGMOID")) {
activation_function = Activation.SIGMOID;
- } else if (args[3].matches("TANH")) {
+ } else if (args[4].matches("TANH")) {
activation_function = Activation.TANH;
} else {
throw new IllegalArgumentException(
"Not correct activation function");
}
- HyperParameters parameters = new HyperParameters(20, learning_rate,
- optimization_algorithm, activation_function);
- NeuralNetwork nn = new NeuralNetwork(parameters);
- MultiLayerNetwork mnn = nn.run("./ressources/webshell_data.json",
- "./ressources/webshell_expected.json");
- System.out.println("Begin K-fold cross-validation");
+ for (int neuron_number = begin_neuron_number;
+ neuron_number < neuron_number_end; neuron_number++) {
+ double average_auc = 0;
+ HyperParameters parameters
+ = new HyperParameters(neuron_number, learning_rate,
+ optimization_algorithm, activation_function);
+ NeuralNetwork nn = new NeuralNetwork(parameters);
- //HashMap<MultiLayerNetwork, Double> map = nn.runKFold(
- // "./ressources/webshell_data.json",
- // "./ressources/webshell_expected.json",
- // 10,
- // 10);
+ HashMap<MultiLayerNetwork, Double> map = nn.runKFold(
+ data_file,
+ expected_file,
+ fold_number,
+ increase_ratio);
+ for (Double d : map.values()) {
+ average_auc = average_auc + d;
+ }
+ try (OutputStreamWriter writer = new OutputStreamWriter(
+ new FileOutputStream("Synthesis_average_AUC.txt", true),
+ StandardCharsets.UTF_8)) {
+ writer.write("Neuron number : " + neuron_number
+ + "Learning rate : " + learning_rate
+ + "Algorithm : " + args[3]
+ + "Activation function : " + args[4]
+ + "Average AUC = " + (average_auc / fold_number));
+ } catch (IOException e) {
+ e.printStackTrace();
+ }
+ }
- NeuralNetwork nnn = new NeuralNetwork(parameters);
- nnn.runCSV("webshell_data.csv");
}
}
--
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