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This video was great as it provided a demo of how one of the methods works while selecting features. I see that the features you were left within your demo were a combination of categorical and numeric/continuous features. I have a couple of questions on this point; a) Will you be applying any further feature selection techniques to the features you had remaining following the filter method demo so that you have the most relevant features that have a high importance score and/or correlation with the output variable before passing them through a few ML classifiers? b) What are the feature selection methods used for supervised learning (binary classification) problem where the input features consists of categorical and numeric/continuous data and the class label is either positive-negative and/or 0-1?
Minutes remaining may be in the period. Seconds remaining may be the shot clock. Maybe shouldn't be added together. Each would provide a different game constraint on the shooter and different information. But good video overall.
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🔥Caltech Post Graduate Program In AI And Machine Learning - www.simplilearn.com/artificial-intelligence-masters-program-training-course?HpPQ6_OU4&Comments&CZcams
🔥IITK - Professional Certificate Course in Generative AI and Machine Learning (India Only) - www.simplilearn.com/iitk-professional-certificate-course-ai-machine-learning?HpPQ6_OU4&Comments&CZcams
🔥Purdue - Post Graduate Program in AI and Machine Learning - www.simplilearn.com/pgp-ai-machine-learning-certification-training-course?HpPQ6_OU4&Comments&CZcams
🔥IITG - Professional Certificate Program in Generative AI and Machine Learning (India Only) - www.simplilearn.com/iitg-generative-ai-machine-learning-program?HpPQ6_OU4&Comments&CZcams
🔥Caltech - AI & Machine Learning Bootcamp (US Only) - www.simplilearn.com/ai-machine-learning-bootcamp?HpPQ6_OU4&Comments&CZcams
This video was great as it provided a demo of how one of the methods works while selecting features.
I see that the features you were left within your demo were a combination of categorical and numeric/continuous features.
I have a couple of questions on this point;
a) Will you be applying any further feature selection techniques to the features you had remaining following the filter method demo so that you have the most relevant features that have a high importance score and/or correlation with the output variable before passing them through a few ML classifiers?
b) What are the feature selection methods used for supervised learning (binary classification) problem where the input features consists of categorical and numeric/continuous data and the class label is either positive-negative and/or 0-1?
Chi squared is pronounced - “Ky squared”. Informative video!
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Great Video! Are there any drawbacks in using Feature Selection?
Minutes remaining may be in the period. Seconds remaining may be the shot clock. Maybe shouldn't be added together. Each would provide a different game constraint on the shooter and different information. But good video overall.
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What about categorical features and numerical independent variable in that case which one to use?
The file named Kobe Bryant remembered me of his demise😢😢
Sorry about that.
@@SimplilearnOfficial Don't be sorry. Remembering the dead is good. I'm sure he would be honored.
How can I classify features based on gain ratio?
Hi, Simplilearn provides online training across the world. We would be happy to help you regarding this. Please visit us at www.simplilearn.com and drop us a query and we will get back to you! Thanks!
Can you send me the Kobe_bryant.csv file?
Please share ppt 🥹