Detecting Parkinson's disease XGBoost
Hello guys,
This is the project about Detecting Parkinson's Disease using XGBoost model.
This is the simple XGBoost Model we can improve it using hyperparameter tunning and features selection.
Kaggle notebook link: https://www.kaggle.com/meetnagadia/de...
GitHub link: https://github.com/meetttttt/Parkinso...
Summary:
In this Python machine learning project, we learned to detect the presence of Parkinson’s Disease in individuals using various factors. We used an XGBClassifier for this and made use of the sklearn library to prepare the dataset.
This gives us an accuracy of 92%, which is great considering the number of data present in the dataset in this project.
You can use Google Colab or Kaggle Notebook where you don't need to look at prerequisite of creating virtual environment and downloading TensorFlow.
🔖 Hashtags 🔖
#detectingdiseaseusingmachinelearning #xgboost #ensemblelearning #python #Parkinson's #machinelearning
My previous video was on Digit Recognition using Deep Learning | In just 30 minutes : • Digit Recognition using Deep Learning...
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LinkedIn: www.linkedin.com/in/meet-nagadia
Hope you find this video insightful,
Have a Great Day,
Happy Learning!!
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