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Use SVM to build and train a model using human symptoms record, and classify cells to whether the symptoms shows Parkinson's Positive or Negative

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Diagnosis-of-Parkinsons

Use SVM to build and train a model using human symptoms record, and classify cells to whether the symptoms shows Parkinson's Positive or Negative

Abstract :

Parkinson’s disease is a progressive nervous disorder that Affects movement leading to shaking, stiffness, and difficulty With walking, balance, and coordination. Parkinson’s symptoms usually begin gradually and get worse over time. Parkinson’s disease usually affects the People who are above 50 years of age. There are also certain cases in which the people with below age 50 also gets affect by Parkinson’s. this particular case is called Young-onset Parkinson’s or (YOPD). In our model, a huge amount of Dataset Is collected from the website called Kaggle which Which contains the symptoms of an Normal people and an People affected by Parkinson’s disease along with Various Parameters. These data is trained using an machine learning Algorithm (or) model (or) Technique called SVM (Support Vector Machine) Classifier. Basically, it is An supervised algorithm which comes under the classification Techniques.

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Use SVM to build and train a model using human symptoms record, and classify cells to whether the symptoms shows Parkinson's Positive or Negative

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