DeepLearning4j Classification using WEKA Java Code

This code classify Iris dataset using DeepLearning4j algorithm using weka in java.

Requirements:

===========

Download all jar files for execute the following java code

Jar files for DeepLearning4j Link -->  https://drive.google.com/drive/folders/1AoHscb4L5ooDtCRZWjg5TakitjuPWKD6?usp=sharing

Datasets

========

IrisTrainingDataset.arff --> https://alljavacodeiknow.blogspot.com/2021/08/iris-training-dataset.html

IrisTestingDataset.arff --> https://alljavacodeiknow.blogspot.com/2021/08/iris-testing-dataset.html

Source Code:

============

Output:

=======

Before execute the java code, add all jar files in your project Libraries

Iris Testing Dataset

 @RELATION IrisTestingDataset

@ATTRIBUTE sepallength REAL

@ATTRIBUTE sepalwidth REAL

@ATTRIBUTE petallength REAL

@ATTRIBUTE petalwidth REAL

@ATTRIBUTE class {Iris-setosa, Iris-versicolor, Iris-virginica}

@DATA

5.1,3.5,1.4,0.2,?

7.0,3.2,4.7,1.4,?

6.5,3.0,5.5,1.8,?

4.9,3.0,1.4,0.2,?

7.0,3.2,4.7,1.4,?

6.3,3.3,6.0,2.5,?

6.9,3.1,5.4,2.1,?

6.7,3.1,5.6,2.4,?

6.9,3.1,5.1,2.3,?

5.8,2.7,5.1,1.9,?

5.6,2.7,4.2,1.3,?

5.7,3.0,4.2,1.2,?

5.7,2.9,4.2,1.3,?

6.2,2.9,4.3,1.3,?

5.1,2.5,3.0,1.1,?

5.7,2.8,4.1,1.3,?

6.3,3.3,6.0,2.5,?

5.1,3.8,1.6,0.2,?

4.6,3.2,1.4,0.2,?

5.1,3.5,1.4,0.2,?

5.3,3.7,1.5,0.2,?

5.0,3.3,1.4,0.2,?

5.7,2.8,4.5,1.3,?

6.3,3.3,4.7,1.6,?

4.9,2.4,3.3,1.0,?

6.6,2.9,4.6,1.3,?

5.2,2.7,3.9,1.4,?

5.0,2.0,3.5,1.0,?

5.9,3.0,4.2,1.5,?

6.0,2.2,4.0,1.0,?

6.1,2.9,4.7,1.4,?

5.6,2.9,3.6,1.3,?

6.7,3.1,4.4,1.4,?

5.6,3.0,4.5,1.5,?

5.8,2.7,4.1,1.0,?

6.2,2.2,4.5,1.5,?

5.6,2.5,3.9,1.1,?

5.9,3.2,4.8,1.8,?

6.1,2.8,4.0,1.3,?

6.3,2.5,4.9,1.5,?

6.1,2.8,4.7,1.2,?

6.4,2.9,4.3,1.3,?

6.6,3.0,4.4,1.4,?

6.8,2.8,4.8,1.4,?

6.7,3.0,5.0,1.7,?

6.0,2.9,4.5,1.5,?

5.7,2.6,3.5,1.0,?

5.5,2.4,3.8,1.1,?

5.5,2.4,3.7,1.0,?

5.8,2.7,3.9,1.2,?

6.0,2.7,5.1,1.6,?

5.4,3.0,4.5,1.5,?

6.0,3.4,4.5,1.6,?

6.7,3.1,4.7,1.5,?

6.3,2.3,4.4,1.3,?

5.6,3.0,4.1,1.3,?

5.5,2.5,4.0,1.3,?

5.5,2.6,4.4,1.2,?

6.1,3.0,4.6,1.4,?

5.8,2.6,4.0,1.2,?

5.0,2.3,3.3,1.0,?

5.6,2.7,4.2,1.3,?

5.7,3.0,4.2,1.2,?

5.7,2.9,4.2,1.3,?

6.2,2.9,4.3,1.3,?

5.1,2.5,3.0,1.1,?

5.7,2.8,4.1,1.3,?

6.3,3.3,6.0,2.5,?

5.8,2.7,5.1,1.9,?

7.1,3.0,5.9,2.1,?

6.3,2.9,5.6,1.8,?

6.5,3.0,5.8,2.2,?

7.6,3.0,6.6,2.1,?

4.9,2.5,4.5,1.7,?

7.3,2.9,6.3,1.8,?

6.7,2.5,5.8,1.8,?

7.2,3.6,6.1,2.5,?

Iris Training Dataset

 @RELATION IrisTrainingDataset

@ATTRIBUTE sepallength REAL

@ATTRIBUTE sepalwidth REAL

@ATTRIBUTE petallength REAL

@ATTRIBUTE petalwidth REAL

@ATTRIBUTE class {Iris-setosa, Iris-versicolor, Iris-virginica}

@DATA

5.1,3.5,1.4,0.2,Iris-setosa

7.0,3.2,4.7,1.4,Iris-versicolor

6.5,3.0,5.5,1.8,Iris-virginica

4.9,3.0,1.4,0.2,Iris-setosa

4.7,3.2,1.3,0.2,Iris-setosa

4.6,3.1,1.5,0.2,Iris-setosa

5.0,3.6,1.4,0.2,Iris-setosa

5.4,3.9,1.7,0.4,Iris-setosa

4.6,3.4,1.4,0.3,Iris-setosa

5.0,3.4,1.5,0.2,Iris-setosa

4.4,2.9,1.4,0.2,Iris-setosa

4.9,3.1,1.5,0.1,Iris-setosa

5.4,3.7,1.5,0.2,Iris-setosa

4.8,3.4,1.6,0.2,Iris-setosa

4.8,3.0,1.4,0.1,Iris-setosa

4.3,3.0,1.1,0.1,Iris-setosa

5.8,4.0,1.2,0.2,Iris-setosa

5.7,4.4,1.5,0.4,Iris-setosa

5.4,3.9,1.3,0.4,Iris-setosa

5.1,3.5,1.4,0.3,Iris-setosa

5.7,3.8,1.7,0.3,Iris-setosa

5.1,3.8,1.5,0.3,Iris-setosa

5.4,3.4,1.7,0.2,Iris-setosa

5.1,3.7,1.5,0.4,Iris-setosa

4.6,3.6,1.0,0.2,Iris-setosa

5.1,3.3,1.7,0.5,Iris-setosa

4.8,3.4,1.9,0.2,Iris-setosa

5.0,3.0,1.6,0.2,Iris-setosa

5.0,3.4,1.6,0.4,Iris-setosa

5.2,3.5,1.5,0.2,Iris-setosa

5.2,3.4,1.4,0.2,Iris-setosa

4.7,3.2,1.6,0.2,Iris-setosa

4.8,3.1,1.6,0.2,Iris-setosa

5.4,3.4,1.5,0.4,Iris-setosa

5.2,4.1,1.5,0.1,Iris-setosa

5.5,4.2,1.4,0.2,Iris-setosa

4.9,3.1,1.5,0.1,Iris-setosa

5.0,3.2,1.2,0.2,Iris-setosa

5.5,3.5,1.3,0.2,Iris-setosa

4.9,3.1,1.5,0.1,Iris-setosa

4.4,3.0,1.3,0.2,Iris-setosa

5.1,3.4,1.5,0.2,Iris-setosa

5.0,3.5,1.3,0.3,Iris-setosa

4.5,2.3,1.3,0.3,Iris-setosa

4.4,3.2,1.3,0.2,Iris-setosa

5.0,3.5,1.6,0.6,Iris-setosa

5.1,3.8,1.9,0.4,Iris-setosa

4.8,3.0,1.4,0.3,Iris-setosa

5.1,3.8,1.6,0.2,Iris-setosa

4.6,3.2,1.4,0.2,Iris-setosa

5.3,3.7,1.5,0.2,Iris-setosa

5.0,3.3,1.4,0.2,Iris-setosa

6.4,3.2,4.5,1.5,Iris-versicolor

6.9,3.1,4.9,1.5,Iris-versicolor

5.5,2.3,4.0,1.3,Iris-versicolor

6.5,2.8,4.6,1.5,Iris-versicolor

5.7,2.8,4.5,1.3,Iris-versicolor

6.3,3.3,4.7,1.6,Iris-versicolor

4.9,2.4,3.3,1.0,Iris-versicolor

6.6,2.9,4.6,1.3,Iris-versicolor

5.2,2.7,3.9,1.4,Iris-versicolor

5.0,2.0,3.5,1.0,Iris-versicolor

5.9,3.0,4.2,1.5,Iris-versicolor

6.0,2.2,4.0,1.0,Iris-versicolor

6.1,2.9,4.7,1.4,Iris-versicolor

5.6,2.9,3.6,1.3,Iris-versicolor

6.7,3.1,4.4,1.4,Iris-versicolor

5.6,3.0,4.5,1.5,Iris-versicolor

5.8,2.7,4.1,1.0,Iris-versicolor

6.2,2.2,4.5,1.5,Iris-versicolor

5.6,2.5,3.9,1.1,Iris-versicolor

5.9,3.2,4.8,1.8,Iris-versicolor

6.1,2.8,4.0,1.3,Iris-versicolor

6.3,2.5,4.9,1.5,Iris-versicolor

6.1,2.8,4.7,1.2,Iris-versicolor

6.4,2.9,4.3,1.3,Iris-versicolor

6.6,3.0,4.4,1.4,Iris-versicolor

6.8,2.8,4.8,1.4,Iris-versicolor

6.7,3.0,5.0,1.7,Iris-versicolor

6.0,2.9,4.5,1.5,Iris-versicolor

5.7,2.6,3.5,1.0,Iris-versicolor

5.5,2.4,3.8,1.1,Iris-versicolor

5.5,2.4,3.7,1.0,Iris-versicolor

5.8,2.7,3.9,1.2,Iris-versicolor

6.0,2.7,5.1,1.6,Iris-versicolor

5.4,3.0,4.5,1.5,Iris-versicolor

6.0,3.4,4.5,1.6,Iris-versicolor

6.7,3.1,4.7,1.5,Iris-versicolor

6.3,2.3,4.4,1.3,Iris-versicolor

5.6,3.0,4.1,1.3,Iris-versicolor

5.5,2.5,4.0,1.3,Iris-versicolor

5.5,2.6,4.4,1.2,Iris-versicolor

6.1,3.0,4.6,1.4,Iris-versicolor

5.8,2.6,4.0,1.2,Iris-versicolor

5.0,2.3,3.3,1.0,Iris-versicolor

5.6,2.7,4.2,1.3,Iris-versicolor

5.7,3.0,4.2,1.2,Iris-versicolor

5.7,2.9,4.2,1.3,Iris-versicolor

6.2,2.9,4.3,1.3,Iris-versicolor

5.1,2.5,3.0,1.1,Iris-versicolor

5.7,2.8,4.1,1.3,Iris-versicolor

6.3,3.3,6.0,2.5,Iris-virginica

5.8,2.7,5.1,1.9,Iris-virginica

7.1,3.0,5.9,2.1,Iris-virginica

6.3,2.9,5.6,1.8,Iris-virginica

6.5,3.0,5.8,2.2,Iris-virginica

7.6,3.0,6.6,2.1,Iris-virginica

4.9,2.5,4.5,1.7,Iris-virginica

7.3,2.9,6.3,1.8,Iris-virginica

6.7,2.5,5.8,1.8,Iris-virginica

7.2,3.6,6.1,2.5,Iris-virginica

6.5,3.2,5.1,2.0,Iris-virginica

6.4,2.7,5.3,1.9,Iris-virginica

6.8,3.0,5.5,2.1,Iris-virginica

5.7,2.5,5.0,2.0,Iris-virginica

5.8,2.8,5.1,2.4,Iris-virginica

6.4,3.2,5.3,2.3,Iris-virginica

7.7,3.8,6.7,2.2,Iris-virginica

7.7,2.6,6.9,2.3,Iris-virginica

6.0,2.2,5.0,1.5,Iris-virginica

6.9,3.2,5.7,2.3,Iris-virginica

5.6,2.8,4.9,2.0,Iris-virginica

7.7,2.8,6.7,2.0,Iris-virginica

6.3,2.7,4.9,1.8,Iris-virginica

6.7,3.3,5.7,2.1,Iris-virginica

7.2,3.2,6.0,1.8,Iris-virginica

6.2,2.8,4.8,1.8,Iris-virginica

6.1,3.0,4.9,1.8,Iris-virginica

6.4,2.8,5.6,2.1,Iris-virginica

7.2,3.0,5.8,1.6,Iris-virginica

7.4,2.8,6.1,1.9,Iris-virginica

7.9,3.8,6.4,2.0,Iris-virginica

6.4,2.8,5.6,2.2,Iris-virginica

6.3,2.8,5.1,1.5,Iris-virginica

6.1,2.6,5.6,1.4,Iris-virginica

7.7,3.0,6.1,2.3,Iris-virginica

6.3,3.4,5.6,2.4,Iris-virginica

6.4,3.1,5.5,1.8,Iris-virginica

6.0,3.0,4.8,1.8,Iris-virginica

6.9,3.1,5.4,2.1,Iris-virginica

6.7,3.1,5.6,2.4,Iris-virginica

6.9,3.1,5.1,2.3,Iris-virginica

5.8,2.7,5.1,1.9,Iris-virginica

6.8,3.2,5.9,2.3,Iris-virginica

6.7,3.3,5.7,2.5,Iris-virginica

6.7,3.0,5.2,2.3,Iris-virginica

6.3,2.5,5.0,1.9,Iris-virginica

6.5,3.0,5.2,2.0,Iris-virginica

6.2,3.4,5.4,2.3,Iris-virginica

5.9,3.0,5.1,1.8,Iris-virginica

Text Classification using Naive Bayes Algorithm in Java, Classifying Text with Naive Bayes Algorithm Java, Spam Detection using Naive Bayes Algorithm

This source code shows how to classify text using Naive Bayes classification algorithm in java.

Requirements:

weka-stable-3.6.10.jar


Source Code:




Output:

In command prompt first set jar file for run using this below line

set classpath=%classpath%;weka-stable-3.6.10.jar;

javac TextClassifier.java

java TextClassifier

Text Classification using SVM Algorithm in Java, Classifying Text with SVM Algorithm Java, Spam Detection using SVM Algorithm

This source code shows how to classify text using SVM classification algorithm in java.


Requirements:

weka-stable-3.6.10.jar


Source Code:



Output:

In command prompt first set jar file for run using this below line

set classpath=%classpath%;weka-stable-3.6.10.jar;

javac TextClassifier.java

java TextClassifier

Text Classification using C4.5 Algorithm in Java, Classifying Text with C4.5 Algorithm Java, Spam Detection using C4.5 Algorithm

This source code shows how to classify text using C4.5 classification algorithm in java. In this example we show spam detection techniques.


Requirements:


weka-stable-3.6.10.jar







Output:

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