Implementation of Neuro-Fuzzy Decision Tree Based Malignant Tumor Detection System

Authors

  • Sanjeev Kumar  ABESIT, Ghaziabad, Uttar Pradesh, India

Keywords:

Breast Cancer, Malignant, Benign, Tumor, RBF, Fuzzy, Decision Tree

Abstract

The paper designs a technique to classify the tumor as malignant or benign. The designed system works on various attributes of tumor like tumor thickness, shape, size etc. The classification process completes in three phases; the phase 1 classifies the attributes as cat1 or cat2 on the basis of information gain. Then in phase 2 cat1 attributes are used to select the class of tumor by using the RBF neural network while the cat2 attributes uses the fuzzy to select the class of tumor. The results of both techniques are collaborated by using the fuzzy inference system in the phase 3. The effectiveness of the technique is easily identified by using results. Finally Comparing accuracy between Neuro Fuzzy system and decision tree.

References

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IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2017-09-30

Issue

Volume 2, Issue 7, September-2017

Section

Research Articles

License

Copyright (c) IJSRCSEIT

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This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Sanjeev Kumar, " Implementation of Neuro-Fuzzy Decision Tree Based Malignant Tumor Detection System, IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 2, Issue 7, pp.08-15, September-2017.