• Dr.PushpaRavikumar
• Swathi H.C
• Priyanka N

Parkinson’s sickness (PD) is one in all the foremost public health issues within the world. It's a well-known proven fact that around a million folks suffer from Parkinson’s sickness. Whereas the amount of individuals affected by Parkinson’s sickness worldwide is around 5 millions. Thus, it's vital to predict Parkinson’s sickness in early stages so early arrange for the required treatment will be created. Feature choice may be a core downside in machine learning. It plays a very important role in creating economical and explainable machine-controlled choices. Sensitive to the initial variety and centers of clusters is one disadvantage of fuzzy c-means cluster methodology. Aiming to reduce the sensitivity, a partial supervision-based fuzzy c-means clustering methodology is planned during this paper. During this methodology, the data is initial clustered with commonplace fuzzy c-means algorithmic rule. If the cluster result doesn’t accord with the structure of knowledge, there should be one or additional clusters that are incorrectly separated leading to some clusters near to one another. The close clusters are often found by investigation the partition matrix. Those close clusters ought to be divided or incorporate. In each things, approaches are then planned during this new methodology to update the appropriate cluster variety and cluster centers. With the updated cluster centers as tagged patterns, partly supervised fuzzy clustering is carried to convey the suitable clusters. Experiments on four artificial datasets and a true dataset show that the proposed cluster methodology has sensible performance by examination to the quality fuzzy c-means cluster methodology. In order to achieve this above objective this paper has been designed to predict Parkinson’s Disease using feature selection and pre-processing techniques like Randomized algorithm and Fuzzy C-means clustering algorithm.

Fuzzy c-means clustering, Randomized feature selection algorithm, Parkinson’s disease, Motor and Non-motor symptoms

"Feature extraction and Pre-processing Technique for Parkinson’s Ailment Recognition ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 8, page no.52-55, August-2021, Available :http://www.jetir.org/papers/JETIREZ06011.pdf

"Feature extraction and Pre-processing Technique for Parkinson’s Ailment Recognition ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 8, page no. pp52-55, August-2021, Available at : http://www.jetir.org/papers/JETIREZ06011.pdf