sir i would like to ask 1 question when we are predicting in MeraLR we are doing dot product of X_test and self.coef_ +se;f.intercept so at that time self.coef shape is (9,1) and X_test shape is (89,10) so how we will do dot product ? because we are excluding the intercept_ from beta
Thank you for this video, Nitish Sir. Sir I am stucked in one place. After creating own class (MyRegression) when calling the fit method, it's showing a long error, showing dtype('o') can't converted to dtype('float64'). Then I've resolved it by converting the X_train and Y_train object type to float64 type before calling the fit method. Then error is solved but the X_test output , coefficients, intercept are coming different compare to the inbuild class. please help Sir.🙏🙏
@@readbhagwatgeeta3810 thank you sir, ya sir beta ka formula meine change kiya tha since thoda wrong tha but still not working, aap please beta ka end formula yaha likh doge kya. So, that i can cross check with mine. Thankyou.
It works actually i tried it. It just that at np.insert(X_train, 1,0,axis=1) try this np.insert(X_train.values, 1,0,axis=1). Because, in this case sir directly took numpy array for X_train, but generally when we split we get X_train as a data frame, so we need to convert it into numpy array to insert another row at the first column.
as i am working on house price prediction ml model from kaggle . will the same approch work for it too. AS I AM HAVING A BIG DIFFERECE BETWEEN r2_score but having exact same reg.coef_ and reg.intercept_ . if anyone know any solution about this plss reply
Bhai woh alag data hai zaroori nahi keh uspe yeh algorithm acha perform kare har data pe har algorithm equally perform nahi karta. it depends upon data type
the only change i did in meraLR class is that i calculated betas in diffferent fashion-- betas=np.dot((np.linalg.inv(np.dot(X.T,X))),(np.dot(X.T,y))) ,by me and by sir betas = np.linalg.inv(np.dot(X_train.T,X_train)).dot(X_train.T).dot(y_train) although same must give same output but i am getting different r2Score plzz clarify the doubt
as i am working on house price prediction ml model from kaggle . will the same approch work for it too. AS I AM HAVING A BIG DIFFERECE BETWEEN r2_score but having exact same reg.coef_ and reg.intercept_ . if anyone know any solution about this plss reply
as i am working on house price prediction ml model from kaggle . will the same approch work for it too. AS I AM HAVING A BIG DIFFERECE BETWEEN r2_score but having exact same reg.coef_ and reg.intercept_ . if anyone know any solution about this plss reply
i'm an experienced data scientist, this guy explain these hard to get topics so easily 🔥, wish i had found your channel sooner !!!
Yes, he explains very smoothly.
I've not seen a teacher like this guy. Truly, an inspiration🔥
i dont comment on any video before but this man is best......for ML
बेहतरीन बहुत बहुत धन्यवाद ❤️🔥🔥
Thank You Sir.
great session Nitish sir
I will spread your videos wherever I can. Underrated channel. Very sad
X_test matrix mein 1 kyu nahi add kiya?, prediction kese horha hai bina uske
sir i would like to ask 1 question when we are predicting in MeraLR we are doing dot product of X_test and self.coef_ +se;f.intercept so at that time self.coef shape is (9,1) and X_test shape is (89,10) so how we will do dot product ? because we are excluding the intercept_ from beta
self.coef is (10,1) that means total(intercept+coff)=11
Sir please take the series forward.
Will be uploading the next video tomorrow.
@@campusx-official yes sir please.
@@campusx-official Yes sir please complete this series
Yes sir please 🥺
Thankyou Sir.
Thank you for this video, Nitish Sir.
Sir I am stucked in one place. After creating own class (MyRegression) when calling the fit method, it's showing a long error, showing dtype('o')
can't converted to dtype('float64'). Then I've resolved it by converting the X_train and Y_train object type to float64 type before calling the fit method. Then error is solved but the X_test output , coefficients, intercept are coming different compare to the inbuild class.
please help Sir.🙏🙏
you are doing great job sir
At 14.05 why do we add self.intercept_ to y_pred?
beta0 + (beta1*X11 + ............betaN * X1M) --> Basically intercept is beta0
why we are using n+1 ??
Sir, Simple Linear Reg mein ye code kaam nhi kr raha hai. I have tried everything, Can you please clarify it. Thank you.
Actually the formula of beta is not correct...there is a correction in that value
@@readbhagwatgeeta3810 thank you sir, ya sir beta ka formula meine change kiya tha since thoda wrong tha but still not working, aap please beta ka end formula yaha likh doge kya. So, that i can cross check with mine. Thankyou.
have you understood how we got output of matrix differentiation?
It works actually i tried it. It just that at np.insert(X_train, 1,0,axis=1) try this
np.insert(X_train.values, 1,0,axis=1).
Because, in this case sir directly took numpy array for X_train, but generally when we split we get X_train as a data frame, so we need to convert it into numpy array to insert another row at the first column.
reshape your x_test and y_test data by X_test.reshape(col_size,1) and y_test.reshape(col_size,1)
why convert to inverse matrix. this scenario i am not understood pls can someone help me
What is R2 score? It is not explained in the video.
that's why you should watch some previous videos
waiting for new video, see u soon.
Tomorrow
as i am working on house price prediction ml model from kaggle . will the same approch work for it too. AS I AM HAVING A BIG DIFFERECE BETWEEN r2_score but having exact same reg.coef_ and reg.intercept_ .
if anyone know any solution about this plss reply
Bhai woh alag data hai zaroori nahi keh uspe yeh algorithm acha perform kare har data pe har algorithm equally perform nahi karta. it depends upon data type
plz make statistic videos
Statistics for Machine Learning: th-cam.com/play/PLKnIA16_RmvbVrE0eZO2bCaFln6jaNq-1.html
done
Why (m+1)(m+1)?
Bcz counting start from 0.......like B0,B1.....Bk then here k+1 term
You are impossible dude in explaining
As in? bad or good?
@@campusx-official good obviously, i have never been this consistent at learning
@@krishnakanthmacherla4431 thanks boss. Keep learning
the only change i did in meraLR class is that i calculated betas in diffferent fashion--
betas=np.dot((np.linalg.inv(np.dot(X.T,X))),(np.dot(X.T,y))) ,by me
and by sir
betas = np.linalg.inv(np.dot(X_train.T,X_train)).dot(X_train.T).dot(y_train)
although same must give same output
but i am getting different r2Score
plzz clarify the doubt
have you figured out the prblm cause i am too having the same problem
it works 🥲
as i am working on house price prediction ml model from kaggle . will the same approch work for it too. AS I AM HAVING A BIG DIFFERECE BETWEEN r2_score but having exact same reg.coef_ and reg.intercept_ .
if anyone know any solution about this plss reply
as i am working on house price prediction ml model from kaggle . will the same approch work for it too. AS I AM HAVING A BIG DIFFERECE BETWEEN r2_score but having exact same reg.coef_ and reg.intercept_ .
if anyone know any solution about this plss reply