Polynomial Regression Machine Learning Python Code

[@TheAIUniversity]

Trivia question from the video: What will happen if we try to increase the value of degree to 3,4 and 5 ?

[@kasifnasim7344]

Increase in degree will lead to over-fitting the model. Resulting to low bias and high variance.

[@venkatramnaidu7555]

@@kasifnasim7344 what is the disadvantages of over fitting

[@venkatramnaidu7555]

over fitting means with 98% accuracy right how come it will be a problem

[@iridescent9204]

​@@venkatramnaidu7555 I'm replying after 3 years but I think you have your answer already. It's accurate for the train data only. For unseen data, that is test data, it may not be that accurate. Hence, low bias (very good prediction for train data) and high variance (possibility of bad predictions on test data).

[@John-vm2zi]

Finally a concise and clear explanation of polynomial regression implementation. Great job.

[@ankushghosh7835]

wow, nice video.........clearing every doubts related to implementation of polynomial regression.

[@TheAIUniversity]

Thanks!

[@maskiinkaal908]

@@TheAIUniversity thanks eng but where I could get the dataset and code of this tutorial for only test purpose

[@saurabhbirari9581]

Explained the concept in such a great way. Hats off.

[@namaste_canadaa]

After a lot of search, i found your video the most helpful one !

[@TheAIUniversity]

Thanks Tarun. Glad you liked the content

[@MrAnandml]

One of the best channel for ML, DL and AI ...you deserve more subs. ..

[@TheAIUniversity]

Thanks Anand

[@narayanareddychinnapureddy1266]

How I missed AI university all these days???😥😥 just_amazing explanation and fabulous content #new_subscriber🙌

[@enricofr7079]

great video, for my friends who read this comment you guys came to the right place

[@johnanih56]

Very informative. You did not evaluate the model by informing us if the model is prone to overfitting or underfitting. Or did you cover that in another video? That is very important. Thanks

[@JyotiSharma-zg1zg]

Good job

[@nirajsathe9220]

As we increase the degree of polynomial the condition of overfitting will occur due to overfitting condition accuracy of test data decreases.......

[@saurabhbhardwaj2576]

Sir, i have 3 input parameters based on these i have a output. How to solve regression in my case.

[@vishnushidling4870]

Thank you sir

[@robertdinan8480]

Great video, very well explained! I was hoping you would be able to help me with the following question. I would like to create an array from a number of predicted values i.e. inserting an array as the input variable where you predict the y-value from the x-value as 53. I am hoping that this can be declared as an array which will hold all of the predicted values. Is this possible?

[@coreymroczkowski8737]

When plotting the polynomial regression model, rather than just getting one blue line, I get many blue lines. Why is this?

[@inteligenciamilgrau]

Me too!!

[@inteligenciamilgrau]

Try to change the split line avoiding shuffle and stratify X_train, X_test, y_train, y_test = train_test_split(X,y,test_size=0.3,random_state=0,shuffle = False, stratify = None) Or, instead, try to predict with the X plt.plot(X,PolyReg.predict(polynom.fit_transform(X)), color='blue')

[@omkumarjha2745]

@@inteligenciamilgrau thanks bhai for solving my problem🙏

[@akmathematicscomputinghub6535]

Can I know from this program what is the exact equation of that regression line ??? Or I will get graph only ???

[@falanshsiddh6753]

How to know what degree to take in PolynomialRegression wrt to data? Why did you took degree 2?

[@nniv1986]

Same question sir ,how we select degree? Is there any method to choose it

[@NotImmortal]

Is there a video with multiple features and multiple features are categorical?

[@TheAIUniversity]

Yes, there is. Pls check out this video: kzbin.info/www/bejne/qIeoi6qfoaZ-ibc

[@anandmohan9642]

Hi, your video helps a lot. Can you help me with the polynomial regression model with multiple variables? Meaning instead of one independent variable we have two or more than two independent variables to find out one dependent variable.

[@MegaPrem1989]

How to identify the degree = 2 in PolynomialFeatures() just by seeing the data or predicting the data with LinearRegression model.?

[@MegaPrem1989]

i mean here how you decided to take the degree as 2 only. why not 3

[@GrowthMindsetGlobal]

Really good. where do i get code

[@CuriousCommunityYT]

Great

[@kalyankrishna5902]

Polynomial regression is possible for multiple linear regression ......

[@pabitrakumarghorai7623]

where is data set

[@TheAIUniversity]

Here you go... github.com/nitinkaushik01/Data_Science_Bootcamp/tree/master/Regression_Algorithms/Polynomial_Regression

[@tussevanamiguel5331]

increasing the degree will lead to overfitting