MLP Classification using WEKA Java Code

MLP is short form for Multi Layer Perceptron algorithm. The multilayer perceptron is the most known and most frequently used type of neural network. On most occasions, the signals are transmitted within the network in one direction: from input to output. There is no loop, the output of each neuron does not affect the neuron itself. Using the backpropagation algorithm for training, they can be used for a wide range of applications, from the functional approximation to prediction in various fields, such as estimating the load of a calculating system or modelling the evolution of chemical reactions of polymerization, described by complex systems of differential equations.

Requirements:

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2 Jar Files

 --> weka-3.7.1-beta.jar

 --> weka-3.7.3.jar

2 Datasets

 --> ClevelandHeartDiseaseTrainingDataset.arff

 --> ClevelandHeartDiseaseTestingDataset.arff

How to Implement:

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ClevelandHeartDiseaseTrainingDataset.arff contains lot of patients Health Records. It has 5 attributes and 1 class attribute.

  1) sex: patient sex (1 = male, 0 = female), 

  2) cp: chest pain type (1 = typical angina, 2 = atypical angina, 3 = non-anginal pain, 4 = asymptomatic), 

  3) slope: the slope of the peak exercise ST segment (1 = upsloping, 2 = flat, 3 = downsloping)

  4) ca: number of major vessels (0-3) colored by flourosopy

  5) thal: (3 = normal, 6 = fixed defect, 7 = reversable defect)

  6) class: (0 = no heart disease, 1 = presence of heart disease)

  

  

This Classification Algorithm classify this training dataset. After Classification, it generate some classification rules. Followed by, this algorithm load ClevelandHeartDiseaseTestingDataset.arff. This testing dataset contains 5 attributes with one class attribute. This class attribute contains (?) question mark. Because we predict each testing record is possible to presence of heart disease or not. Then this classification algorithm predicts each records class attribute value based on classification rules (It is generated after Training Process).

How to Run this Code in Command Prompt:

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>set classpath=%classpath%;weka-3.7.1-beta.jar;

>set classpath=%classpath%;weka-3.7.3.jar;

>javac MLPClassification.java

>java MLPClassification

Output: MLPOutput.txt