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

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  • Sanjeev Kumar

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.

Suggested Citation

  • Sanjeev Kumar, 2017. "Implementation of Neuro-Fuzzy Decision Tree Based Malignant Tumor Detection System," International Journal of Scientific Research in Computer Science, Engineering and Information Technology, International Journal of Scientific Research in Computer Science, Engineering and Information Technology, vol. 2(7), pages 08-15, September.
    • Handle: RePEc:jbh:ijsrcs:v2:y2017:i7:id:hcseit174402
    Note: Article URL: https://ijsrcseit.com/CSEIT174402
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