• P.Laura Juliet
• Dr. P.R.Tamilselvi

Liver disease (LD) is viewed as the most prevalent type of chronic liver disease around the world. The prediction of liver disease is an important factor for successful treatment and diminish genuine health results. Thusly develop a prediction model based on machine learning algorithms. A dataset was created with ten attributes that included 994 liver patients wherein 533 patients were females and others were male. This paper analyzed Random Forest (RF), Support Vector Machine (SVM), Bayesian Network (BN), and Naïve Bayes (NB) prediction algorithms. The performances were evaluated with Detection, Classification and Intensity.

Classification, intensity, Prediction, Detection, Liver Disease.

"ANALYSIS ON EARLY PREDICTION OF BREAST CANCER USING DIFFERENT ALGORITHMS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.602-610, June 2019, Available :http://www.jetir.org/papers/JETIR1907H88.pdf

"ANALYSIS ON EARLY PREDICTION OF BREAST CANCER USING DIFFERENT ALGORITHMS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp602-610, June 2019, Available at : http://www.jetir.org/papers/JETIR1907H88.pdf