• Prakash
• T. Ragul Vijay
• K. Arun
• H. Arun Kumar

Treatment options for cancer are numerous and varied. The kind of cancer, its stage and intensity, and most significantly, genetic variability, all affect the recommended course of treatment for a given patient. The targeted medication therapies are likely to react differently or not at all in such a complicated environment. To investigate the reaction of anti cancer drugs, we must comprehend malignant profiles. The information contained in these carcinogenic profiles may help identify the underlying causes of the spread of cancer. Therefore, it is necessary to analyse cancer data in order to forecast the best course of treatment. Such profiles can be analysed to predict and identify possible therapeutic targets. The primary goal of this work is to present a machine learning-based cancer profile classification method.

"ANALYSIS AND PREDICTION OF CANCER DATASET ON CANCER DATASET", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 3, page no.i448-i450, March-2024, Available :http://www.jetir.org/papers/JETIR2403856.pdf

"ANALYSIS AND PREDICTION OF CANCER DATASET ON CANCER DATASET", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 3, page no. ppi448-i450, March-2024, Available at : http://www.jetir.org/papers/JETIR2403856.pdf