COMPARATIVE STUDY OF GENETIC AND RANDOM FOREST ALGORITHM ON BONE MARROW GENE SEQUENCES

Bone marrow cancer is formed inside the spongy tissue found in the centre of bone. In Humans bone marrow are located in the ribs, vertebrae, sternum, and bones of the pelvis it contains stem cells that form into numerous types of blood cells found in the body namely red blood cells, white blood cells and platelets. When these cells grows too fast or abnormally results in Bone marrow cancer. DNA sequencing is the process of finding the accurate order of nucleotides in chromosomes and genomes. The development of techniques to store and search DNA sequences has led to widely applied methods especially string matching algorithms, machine learning and database theory. In this research work gene sequencing of bone marrow cancer is used to analyze and evaluate the performance of data mining techniques. The proposed work focused on comparative study of data mining algorithms. The Random forest and genetic algorithm were used as the evaluation indicators for the comparative study of the execution time and memory efficiency of each algorithm. The performance is analyzed based on the different number of instances and confidence in gene sequence data set.