This was pretty dense with information. Note that my prior here was a Normal distribution, and I used arbitrary constants of a = 0.1, b = 0.1, g = 10.. Once you get to the coding demonstration, I highly recommend that you pull up the code + data to follow along. The code can be retrieved here: github.com/SpencerPao/Data_Science/tree/main/Bayesian%20Regression
Thank you Spencer for this great piece of work. I would really appreciate it if you could share reference for the theoretical background. I need mathematical expressions to include it in my current work.
Great video, your explanation is very clear. I am confused in how you got the values in the logit_loan_default column? Does it need to have binary values in this field?
In the example I used, you can definitely just have categorical variables (0,1). You'd just have to change your distribution to that of Bernouli (2 outputs) The values I have are essentially centroids for each given cluster. (Check out the kmeans_data.r script I have on github). So, in essence, I am doing a regression to fit the normal. Some additional information can be found here: bayesball.github.io/BOOK/bayesian-multiple-regression-and-logistic-models.html#bayesian-logistic-regression I hope that helps!
How long did it take you to learn to do all this stuff in R and really understand what you are doing? I want to really master this type of stuff using R but do not feel as comfortable with it all (the code and the theory) as I would like to. I am about to get my undergraduate degree in econ and math, then my masters in econ and have been practicing in R for about a year and practicing statistical theory for about 6 months.
Its a journey! I learned all my basic stuff in college (4 years) and the more advanced stuff while working. I learned R in college and all the python stuff was in industry. 6 months is not that much but around the 1 year mark of continuously using the language: R (or any programming language for that matter) and you’ll be just fine!
Hi Spencer, could your share the R code for how you k-mean'd the data to generate Kmeans_scaled_data100.csv?Did you run a logit regression 1st using glm to generate your logit_loan_default field? Thanks Alex
I uploaded the kmeans code to my github repository with some sample data. (The original dataset is too large). The binary outcomes already came as is, so I did not do any glm related functions.
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This was pretty dense with information. Note that my prior here was a Normal distribution, and I used arbitrary constants of a = 0.1, b = 0.1, g = 10.. Once you get to the coding demonstration, I highly recommend that you pull up the code + data to follow along.
The code can be retrieved here: github.com/SpencerPao/Data_Science/tree/main/Bayesian%20Regression
New sub, enjoying your channel so far!
Very well explained. Thanks!
omg❤ this really saved my life!!! Thank you so much!!! can't believe I could use the model right now❤❤❤
Thank you Spencer, for sharing this great video! It will help a lot to understand bayesian regression
Just finding your channel now, you're of great help! Thank you so much sir! :)
Thank you Spencer for this great piece of work. I would really appreciate it if you could share reference for the theoretical background. I need mathematical expressions to include it in my current work.
Since you post your like/dislike count, here's a like from me. The video was great btw
Thanks sir, is there a written document explaining this?
Great video, your explanation is very clear. I am confused in how you got the values in the logit_loan_default column? Does it need to have binary values in this field?
In the example I used, you can definitely just have categorical variables (0,1). You'd just have to change your distribution to that of Bernouli (2 outputs)
The values I have are essentially centroids for each given cluster. (Check out the kmeans_data.r script I have on github). So, in essence, I am doing a regression to fit the normal.
Some additional information can be found here: bayesball.github.io/BOOK/bayesian-multiple-regression-and-logistic-models.html#bayesian-logistic-regression
I hope that helps!
Not sure how you clustered with K Means? Is it so that you can apply bayesian to different clusters separately?
Thank you for your video it so helped to me on my school project appreciate that🙏🏻🙏🏻👏🏻
I'm glad I helped! :)
How long did it take you to learn to do all this stuff in R and really understand what you are doing? I want to really master this type of stuff using R but do not feel as comfortable with it all (the code and the theory) as I would like to. I am about to get my undergraduate degree in econ and math, then my masters in econ and have been practicing in R for about a year and practicing statistical theory for about 6 months.
Its a journey! I learned all my basic stuff in college (4 years) and the more advanced stuff while working. I learned R in college and all the python stuff was in industry. 6 months is not that much but around the 1 year mark of continuously using the language: R (or any programming language for that matter) and you’ll be just fine!
@@SpencerPaoHere thank you !:)
Hi Spencer, could your share the R code for how you k-mean'd the data to generate Kmeans_scaled_data100.csv?Did you run a logit regression 1st using glm to generate your logit_loan_default field?
Thanks Alex
I uploaded the kmeans code to my github repository with some sample data. (The original dataset is too large). The binary outcomes already came as is, so I did not do any glm related functions.
The video is too blurred, i can't see it clearly.
Weird. This video goes up to 1080p. You might have to wait for the buffer to go through. (And select the appropriate setting)
Do we need to use cross-validation in bayesian analysis to control overfitting?
Nope. They are fundamentally different. (Bayesian has MCMC that comes into play)
@@SpencerPaoHere Then bayesian models can't overfit if they have too many parameters or very few observations?
@@juanete69 it most certainly can! Though the sampling will address the overfitness of the model to the best of its ability via MCMC
@@juanete69 it most certainly can! Though the sampling will address the overfitness of the model to the best of its ability via MCMC
Nice meme 3:31 lol
😂
can this be used to predict forex markets reversals?
You could try! Though, I've personally never tried this technique on forex, so I can't comment on how well it'd do.
I see one punch man pretty cool
Ayyyyyy :)