HYBRID NON LINEAR CA FOR BONE CANCER PREDICTION

Abstract

Cancer prediction is a difficult problem to predict in the real world. The reason and purpose behind extraordinary spread of this malady is exceptionally hard to get it. We have different structures and sorts of tumors, a unique model to foresee malignancy is troublesome. Albeit numerous papers are accessible to follow malignant growth, there is still space for advancing another procedure for anticipating disease. We propose a novel Hybrid Non Linear CA based acquainted memory which gains from different contextual investigations breaking down the information and predicts the Bone Cancer. We have taken datasets from ICCR Datasets and handled them utilizing Hybrid Unsupervised learning calculation. Fundamental work was done and we have contrasted our work and some standard existing writing. The proposed classifier execution was discovered promising.