Feature Selection Techniques on Parkinson’s Dataset скачать в хорошем качестве

Feature Selection Techniques on Parkinson’s Dataset

Applying multiple Feature Selection techniques on the Parkinson’s Disease dataset to identify the most important features for accurate disease prediction. Methods like Variance Threshold, Correlation, Chi-Square, Mutual Information, Relief help remove irrelevant and redundant features, improving model performance. --- 💻 Source Code & Notebooks: https://github.com/edumentordeepti/Fo... --- ⏱️Chapter/TimeStamp⏱️ 00:00 - intro 01:01 - how to import whole libraries? 03:40 - how to understand parkinson's disease dataset? 07:00 - how to preprocess categorical columns? 08:42 - how to get independent and target variables? 09:55 - how to get model accuracy without feature selection methods? 12:10 - how to implement variance threshold? 16:08 - how to implement correlation coefficient? 21:28 - how to implement chi-squared test method? 23:28 - how to implement mutual information method? 24:20 - how to implement relief algorithm? 26:02 - how to compare all methods together? 26:53 - how to get final accuracy of model after feature selection? 28:19 - outro --- ▶️ Channel Link : https://www.youtube.com@EduMentorDeepti 📚 Playlists: ▶️ Complete AI and ML: https://www.youtube.complaylistlist=PLJHzgC_PCyXx3KWBK_P4hi_-BNEryZc2m ▶️ Machine Learning: https://www.youtube.complaylistlist=PLJHzgC_PCyXytx6o8Rm62PR_qkQZC2t0g ▶️ Data Science: https://www.youtube.complaylistlist=PLJHzgC_PCyXxe4v_H2iuC6hSWBfs6BsNJ ▶️ Python for AI: https://www.youtube.complaylistlist=PLJHzgC_PCyXyLv-DeF4kpBFgrvHhWUm5j --- ✉️ Email Us – edofficialac@gmail.com --- #FeatureSelection #MachineLearning #DataScience #ParkinsonsDisease #FeatureEngineering #DimensionalityReduction #VarianceThreshold #Correlation #ChiSquareTest #MutualInformation #ReliefAlgorithm #RFE #MLProject #PythonMachineLearning #ScikitLearn #AIInHealthcare #DataScienceTutorial #PredictiveModeling #MLAlgorithms #DataAnalytics #edumentordeepti #edumentor #deepti --- DISCLAIMER This video is created for educational purposes only. We do not own any copyrights, all code, resources shared are for learning only and all rights go to their respective owners. Please respect licenses and terms of use when implementing in your projects. The usage is non-commercial and we do not make any profit from it. The sole purpose of this vides is to Learn & Grow... together in the field of Artificial Intelligence and Machine Learning..