Difference Between fit(), transform(), fit_transform() and predict() methods in Scikit-Learn

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3 жыл бұрын

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Пікірлер: 138

@jammerules80 3 ай бұрын

Thank you for the clear explanation. I spent $10K learn ML-AI from UC Berkeley and yet I could not understand this concept before this video. Job well done!

@mariuszwiesiolek9340 2 жыл бұрын

This was fantastic, I really got the essence of not only when, how, and why to use fit(), transform(), fit_transform(), predict() but in the context I was looking for!

@nigamaveena4211 3 жыл бұрын

I always get confused about fit() ,transform(), fit_transform()....thank you sir... you are like a saviour to many people like me...

@cocgamingstar6990 Жыл бұрын

Still not got

@pratikghute2343 Жыл бұрын

@@cocgamingstar6990 see bro, first of all we use .fit in two scenarios first one is at time of scaling and second one is at models training. (scaler.fit_transform(xtrain) and scaler.transform(xtest) that is part of Data preprocessing step and the second scenario we use .fit is at model training (model.fit(xtrain)) there we use fit to fetch the parameters like slope and y intercept.

@survivor9367 3 жыл бұрын

Actually I am searching for this in on other videos. As it is not available in you lr play list.. You just updated.. Thank you so much sir

@alessandrodf888 3 жыл бұрын

Batman, Superman and Krish Naik

@devinpython5555 3 жыл бұрын

summary of this is (intuition) for train data: fit creates formula for all the features in dataset ,transform will transform data with created formula. for test data: formula already created just transform it accordingly.

@srujankumar637 2 жыл бұрын

But on test data fit( ) has not applies then how it gives transform( ) value,,, Because mean(mu) and st.dev has to Calculated for test data by using fit ( ).

@srujankumar637 2 жыл бұрын

Or data distribution is almost same for both train and test data so that's why mean and st.dev is same for train and test data... And once we got values for train by using fit () that will be transformed for test data ????

@abdulrahiman8111 2 жыл бұрын

Hi Krish. Your video was really informative and helped me understand the requirement as well as the difference between fit(), transform(), fit_transform() very well. Thank you

@rohitkatkar3736 2 жыл бұрын

I was not clear with, why fit_transform for train data and only transform for test. Now i understood this concept. Thank you!!!

@jiaxinxie8794 2 жыл бұрын

This is clear, in-depth, comprehensive, and helpful! Thank you so much!

@gomathic9557 3 жыл бұрын

it is very useful video krish, now i got a clear information about fit and transform thanks giving this useful information krish .

@ashraf_isb Ай бұрын

old videos are gold, thanks for this krish

@harikrishna-harrypth 3 жыл бұрын

Krish, you are a LEGEND!!!!!!!!!!!! Thanks much for making these enlightening tutorials!!!!!!!

@akshayg.p8201 Жыл бұрын

Krish sir , I got lots of idea on fit(), transform(), fit_transform() and predict() methods. Thanks a lot.

@jamalhasanzakarneh9837 3 жыл бұрын

Thank you Krish; it is just another beautiful video of your very helpful videos

@AromonChannel 3 жыл бұрын

Thank you so much krish naik! i've been trying to understand this and you explain it in the very easy way, so we can easily understand it, thank you!!!!!!!!!!!!!!!!!!!!!

@notmimul 2 жыл бұрын

God bless you!!! Your videos make everything simple.

@01kumarr 2 жыл бұрын

Just in one sort u cleared all doubts. Thanks 👍

@biswajitnayaak 2 жыл бұрын

Crystal clear and detailed . Awesome. Keep it up

@Annisa-yc5zp 2 жыл бұрын

Hello, you're such a good teacher! This helped me a lot. Thank you!

@nguyenthituyetnhung1780 9 ай бұрын

So clear explanation that i can also understand process of machine learning. Thanks a lot

@suvamgupta2914 2 жыл бұрын

Hats off sir!! Your explanation is of God level 💯 Thank you sir ❤️

@optimusagha3553 2 жыл бұрын

Simple and straightforward! Thanks!!👏

@parikshithh4991 3 жыл бұрын

Beautifully Explained

@aishwaryanarkar2954 3 жыл бұрын

THANK YOU KRISH AMAZINGGGG BLESSINGS TO YOU

@shashikarathnasinghe1241 2 жыл бұрын

Thank you soo much ,, was struggling to understand this concept .superrr well explained

@eitanshirman9072 2 жыл бұрын

Thank you so much for such a brilliant explanation!

@shaelanderchauhan1963 3 жыл бұрын

Thanks a lot you have contributed a lot to this community

@theforester_ 2 жыл бұрын

awesome video thanks very much. big shout out to all indians out there helping out the world. big greetings from brazil

@zaindeen4490 3 ай бұрын

Thank you so much krish sir. It was quite informative! I was searching for this kind of video but wasn't able to find it Thanks for all of your great efforts ❤

@ajaykuruba1738 3 жыл бұрын

Hi Krish It would be really helpful if you create a playlist on tensorflow serving and tensorflow lite.

@doumansarouei6994 2 жыл бұрын

Thank you so much for all of the valuable content you shared!

@soajack 3 жыл бұрын

Clearly Explained ! Thanks a lot !!!

@saurabhbarasiya4721 3 жыл бұрын

Thanks for this

@bkpusprajkumar8744 3 жыл бұрын

Thank you so much, sir for this lecture.

@gangeshwarinetam413 2 жыл бұрын

thank you sir ..I always get confused but now its clear. Thank you soooo much

@pavanviswanadhapalli3512 Жыл бұрын

compared to all other channels ], your classes are so detail and very understandable, so sir please can you make a complete vedio on pca...? please sir

@bhargavikoti4208 3 жыл бұрын

Finally😁..Thanks for uploading

@robertoespinoza199 3 жыл бұрын

thanks so much for the value of your videos 💯💯

@saheedajayi7352 2 жыл бұрын

Again, Thank you Krish, well explained.

@rishabhkumar-qs3jb 3 жыл бұрын

Awesome explanation :)

@muhammadzeerakkhan6300 3 жыл бұрын

Great explanation and intuition (Y)

@Harshpatel-uw2dw 4 ай бұрын

it amazing video i had come through a great understanding and very easy to understand the concept thank you sir

@pranaypakhale 3 жыл бұрын

Can you please make video on different types of transformation viz standardscaler, minmaxscaler etc and when to use which

@ayaansk99 2 жыл бұрын

Its very helpful video sir Thanks for guiding

@ajayjaadu42 Жыл бұрын

Sir you explain so good .Thankyou for this

@jlxip 3 жыл бұрын

Thank you so much, this helped me a lot :)

@sabaamanollahi5901 2 жыл бұрын

Excellent Explanation !!!!

@akshitagoel3099 2 жыл бұрын

Well Explained. Really very informative. Thankyou so much :)

@darshanayenkar Жыл бұрын

you have cleared my concept

@KiranGunda-ph7df 2 ай бұрын

Superbbb explanation brother...

@bluejadoo6912 Жыл бұрын

thank you for clearing my doubts sir

@heliyahasani6859 2 жыл бұрын

I love you man you are a game changer god bless you please load more videos

@adipurnomo5683 2 жыл бұрын

Classifier algorithm whose using distance usually do normalize the datasets before put to model

@BytemeMaybe 7 ай бұрын

amazing explanation, thx bro

@louerleseigneur4532 3 жыл бұрын

Thanks Krish

@oyesinghji7910 2 жыл бұрын

hi krish, can you make a full video of how to do deployment full process video, including all steps.

@hiral9591 2 жыл бұрын

It's amazing👍

@shivu.sonwane4429 3 жыл бұрын

Fit_transform use on training data but transform only on testing /new data Applies the same transformation to both set of data which creates consistent column and prevent data leakage it means learning something from testing data this is not allowed

@hanscesa5678 Жыл бұрын

So where should you use fit(), transform(), fit_transform() during a K-Fold Cross Validation? Before CV or During CV?

@shivamshinde9810 2 жыл бұрын

very helpful!! Thanks!!

@tonnysaha7676 3 жыл бұрын

Thank you very much sir🙏

@naeymaislamph.d9976 2 жыл бұрын

Excellent!

@mangkhongsai9029 Жыл бұрын

Thank you so much...

@vanditha07 3 жыл бұрын

Thank you so much!!

@1111Shahad 2 жыл бұрын

Thank you Krish

@rkkcode 2 жыл бұрын

Thank you .

@adityasharma5876 3 жыл бұрын

Hi Krish please make a video on difference between map(), flat_map() and apply() in tf.Dataset

@anirbanc88 Жыл бұрын

superb

@priyadarshanr9950 2 жыл бұрын

Sir , I can understand that it formats the test data in the same format of train_data , but how does transform function helps to overcome overfitting,

@sanyamsharma3940 2 жыл бұрын

You are amazing !

@arshad1781 2 жыл бұрын

Nice 👍

@kumarprince5054 3 жыл бұрын

Thanks

@aryankaushik3761 2 жыл бұрын

Thank you sir

@paulkang2806 2 жыл бұрын

if you are fitting, and transforming for the scalers and normalization, and you fitted (mean, stdev) for the training data, and say if you are applying it to the test data, isn't that something related with data leakage?

@tatendaVIDZ90 2 жыл бұрын

this is beautiful

@milliesadie486 Жыл бұрын

thank you

@kiranvanukuri9382 3 жыл бұрын

Plz make video on image recognition in jupyter note book and deployment technique with deep explanation

@manishaundale7458 2 жыл бұрын

If the train data and test data unique values are different then how can we apply label encoder with fit and transform?

@krishnabhadke6161 2 жыл бұрын

nice sir

@rezapourbahreini4473 2 жыл бұрын

thank you for your tutorial. There's one serious issue that I want to address here. As far as I know, we're not allowed to do anything that results in leakage from test data to train data. So when you do a fit_transform on a train_data and save the parameters in the scaler, it's okay to do scaling on the test data based on that very scaler, but not the other way around!! Because there would be a leakage for mean and s.d from train data to test. This way always the result would be better but it's because of the cheat that is happening and the model really. So be careful with the order of steps you go through when scaling train and test data.

@swethanandyala Жыл бұрын

I too feel the same...we have to fit and transform on the test data also..to avoid data leakage

@omsonawane2848 Жыл бұрын

what if we fit on whole data and then split and transform train and test data. This way test data will not depend on training parameters. also no data leakage will occur

@subhashvarma4551 3 жыл бұрын

sir, if we apply the same mean in transforming the test data as in train data, this may be the case of data leakage where we are leaking information of train to test. which might not be preferable in the real-time scenario as future data should be totally anonymous to the train data. we should also perform a fit transform on the test data in such cases. Need your thoughts on this.

@mouleshm210 3 жыл бұрын

No bro, we should be cautious only on the data leakage from test to train data where, future data parameters like mean or min/max values must not be leaked while doing preprocessing, thats why we do only transform() in test data.

@naiduvinay4911 2 жыл бұрын

Thank You, understood

@bivasbisht1244 Жыл бұрын

amazing

@akashkumar-bq7cl 3 жыл бұрын

hi krish ,what will happen if i apply fit_transform to my test data as well?what will be the outcome?why shudnt we do it?is it because new mean and sd will be calculated for the test data?but we need the same mean and sd and formula of the train data to be applied to the test data aswellright?is that the reason we use only transform?just did not get this part and the rest of the video im so happy that so much content in just half an hour that too for free,GOD BLESS YOU PLEASE HELP

@munawarabbasi9683 Жыл бұрын

Thanks for making it a complete halwa.

@preetamchakravarty Жыл бұрын

Can you state the screen recording software and the settings you have used for this recording? Thank you.

@RAHUDAS 2 жыл бұрын

Where to put outlier detection in ur data processing chain ??

@adipurnomo5683 2 жыл бұрын

13:46 sir, what the real world application when we don't use test data instead we use unseen data. Is the data from unseen data need to be normalize before put into model?

@pragavipul1563 2 жыл бұрын

what is the writing pad you use ?

@gunamrit 2 жыл бұрын

magician!

@harshagrawal5613 3 жыл бұрын

100℅ clear

@yashub9580 Жыл бұрын

sir can you please tell me how to resolve this error "Deprecated distribution is specified in `adstock__tv_pipe__carryover__strength` of param_distributions. Rejecting this because it may cause unexpected behavior. Please use new distributions such as FloatDistribution etc."

@frankdearr2772 2 жыл бұрын

Hi, I understood about well what you told, but could you tell me WHY y_train is not scaled like X_train ??? For me that is because values are like false or true , if the y_train values were different like 10, 5 , 41, 5.8, etc , I think I will have to scale y_train ?? Please show me the way for that small question about your video :)) Thanks for your great video about that topic Laurent

@kavanadeshpande9690 Жыл бұрын

Hi, as per my knowledge, scaling of dependent feature is not necessary when we have less cardinality for classification problem. For regression, if we scale the dependent feature then automatically Mean Square Error will also get scaled.

@frankdearr2772 Жыл бұрын

@@kavanadeshpande9690 Thanks, great information. That give me the right way to go ahead. Please have a nice day :) Laurent

@frankdearr2772 Жыл бұрын

@@kavanadeshpande9690 Hi, thanks a lot for your answer.. I understand better now :) Please have a nice day Laurent

@unmeshmandal3071 2 жыл бұрын

What if first I scale the whole X table and then split using train_test_split?

@soukainahanafi1685 3 жыл бұрын

I understand that but with a polynomial model we use fit_transform and not only fit .It' hard to understand . ##this is the example that I'm working on pr = PolynomialFeatures(degree=5) x_train_pr = pr.fit_transform(x_train[['horsepower']]) x_test_pr = pr.fit_transform(x_test[['horsepower']])

@sherin7444 2 жыл бұрын

Before calling train test split why we didn't scale our data?

@SUMITKUMAR-qi6mz 3 жыл бұрын

I am having experience of 1 year in customer service in BPO but I want toh become Data scientist . But I'm having difficult toh get job in same because they are asking for experience in data science. Pls help me how to portrait my resume to get job

@khaboninamasemola1970 2 жыл бұрын

You saved my backside with this video. Thank you.

@nagamohan1412 3 жыл бұрын

Hi krish, I am Naga Mohan. I want to use data science or data analyst technology for my fathers agriculture land but I don't how to start actually I am so much confused. I have no data. I don't know how to create my own data for my farm land. Can you please give me tips. How to start the project and how to create the data. We have 2 acres of paddy land and 2 acres of banana land