Handling skewness

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Handling skewness

Рет қаралды 29,336

Sukamal Das

Күн бұрын

Пікірлер: 52

@bitanbanerjee2090 3 жыл бұрын

Wow I was confused about this and you explained it so well!!!! Thank you

@teja2683 2 жыл бұрын

Today I learned so many things from you bro

@CoopmanGreg Жыл бұрын

😀There was no skewness in the opinion of your watches. They were unanimous in that it was a GREAT video. I definitely agree. Thanks.

@visvashattri 3 жыл бұрын

Thank you.. it was indeed helpful :)

@freeprivatetutor 8 ай бұрын

❤ and hug. ❤❤❤❤.

@alok94singh 2 жыл бұрын

nice explanation sir, keep posted these kind of informative videos

@mkeremyucedag 3 жыл бұрын

Hello from Turkey! That's great content. I'd like to ask you what if our target (y) is skewed what to do then ? For example let's say I made a car price prediction model and variables are horsepower of car and color of car and car price is skewed in dataset. I did sqrt or log to car price and trained the model, got the mse and did model tuning everything is finished. And now I want to see a 180 hp black car's price. If I insert the values it will give me the sqrt'ed or log'd value right ? So if I do the reverse of log or sqrt will it give me the real car price ? Or should I do other operations ? Thank you...

@sukamal_das 3 жыл бұрын

Hello, if the target is skewed, you can apply log or sqrt transformation. Now the predicted value you get is not original price value, it is either sqrt or log of the price. To get the actual price from predicted value, you can apply the inverse function, for eg if transformation is square root, apply square or if transformation is log (base e) apply exponential function i.e np.exp(). I hope that helps, Thank you.

@mkeremyucedag 3 жыл бұрын

@@sukamal_das Oh now it's very clear for me. Thank you so much your contents are great. Sincerely...

@Sallu0123 3 жыл бұрын

Thanks for the videos, where is the descriptive stats videos

@sukamal_das 3 жыл бұрын

statquest and khan academy videos are good.

@HariMithra-iz7oq 3 ай бұрын

Hi. Can you please take me a paid tutorial for a case study of australian vehicle prices from kaggle? Just one session will be enough.

@mamatha1850 Жыл бұрын

your video is helpfull.you r saying that highly correlated features with the target.we no need to perform any transformation.will this impact the accuracy of the model.plz reply

@ketanbutte3497 Жыл бұрын

Hi Sukamal, great explanation. For symboling, can we convert the scale to min-max(0-1) and then apply sqrt?

@michaelogunmakin9143 2 ай бұрын

subscribed, thank you!

@adamleyon8297 3 жыл бұрын

absolutely useful video, thanks for sharing!

@charmilam920 3 жыл бұрын

great video

@ajaykushwaha-je6mw 3 жыл бұрын

conceptual knowledge is very good, you have earned 1 more subs. There is one just improve your playlist, rest are good.

@pforpython7884 Жыл бұрын

Could you please share the link for Descriptive Statistics Video?

@preciousbatta9576 2 жыл бұрын

Very helpful.. Thanks I also want to ask if we reduce skewness, is there any need to scale the data as well?

@sukamal_das 2 жыл бұрын

Yes scaling is still required.

@shama6345 3 жыл бұрын

How can we remove negative and positive skewness together?

@sukamal_das 3 жыл бұрын

Skewness can be either positive or negative, if positive apply square root, logarithm, if negative - apply square, cube or higher powers.

@shama6345 3 жыл бұрын

Plz make video on that

@AbhishekSingh-og7kf 3 жыл бұрын

very useful video, thank you for sharing.

@AshishYadav-vi6on 2 жыл бұрын

very well explained!

@AbhishekRana-ye9uw 3 жыл бұрын

sir how do i find skewness of a list given as price = [14751, 16422, 15398, 9445, 12589, 11687, 10692, 8475, 11184, 9961, 12898, 11905] please do reply sir will be very helpful :-)

@sukamal_das 3 жыл бұрын

from scipy.stats import skew import seaborn as sns price = [14751, 16422, 15398, 9445, 12589, 11687, 10692, 8475, 11184, 9961, 12898, 11905] # print skewness value skew(price) # plot distribution sns.distplot(price)

@AbhishekRana-ye9uw 3 жыл бұрын

@@sukamal_das thank you sir you are great👍🙏

@JVJBA Жыл бұрын

Hi can you pls share the video for discriptive statistics ?

@rohinisn8147 4 жыл бұрын

Tq sir....🙆‍♂️

@sktdebnath 2 жыл бұрын

Very very useful.

@pranavkhurud6254 Жыл бұрын

Hello DAS Sir, Could you please help me or provide here a descriptive statistics video link. Not able to find out. Any update

@pranavkhurud6254 Жыл бұрын

Anu update

@RashmiUdupa 3 жыл бұрын

Instead of removing skewness, would removing outliers be enough?

@sukamal_das 3 жыл бұрын

Can't say that, but removing outliers will definitely reduce the magnitude of skewness, but no guarantee on totally removing the skewness. Skewness and outliers are 2 different things, A normal distribution with 0 skewness can have outliers on both the extreme ends.

@ajaykushwaha-je6mw 3 жыл бұрын

removing outliers by trimming is removing records which comes in outlier i.e. you are loosing the data. removing outliers with capping is good practice and you can try, it works very well.

@pinkyeeeepinkydas 2 жыл бұрын

in heat map one feature has 0.002, 2nd has 0.0017.when i am going to skew, getting negative values for 2nd one -0.07723174570350672 where in first 0.2155809290498895. is it correct. why -ve values comming