Tutorial 44-Balanced vs Imbalanced Dataset and how to handle Imbalanced Dataset

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Tutorial 44-Balanced vs Imbalanced Dataset and how to handle Imbalanced Dataset

Рет қаралды 42,265

5 жыл бұрын

Here is a detailed explanation about the balanced vs imbalanced dataset and how to handle the imbalanced dataset.
#balancedvsimbalanceddataset
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Пікірлер: 61

@sushantapanda4589 5 жыл бұрын

You are a great tutor, the way you are explaining, great to see you holds to the subject. Awesome

@louerleseigneur4532 3 жыл бұрын

Thanks Krish

@shahnawazkhan1636 3 жыл бұрын

Great sir there is no need to join any institute to learn the Data Science just follow the Krish Naik sir playlist.

@mayurkhandeshe4813 4 жыл бұрын

your teaching is very effective sir.... very easy to understand

@arjyabasu1311 4 жыл бұрын

Upto what ratio should we consider it as a balanced dataset ??

@arjyabasu1311 4 жыл бұрын

@Kushal Hu what ratio that is?

@venkataraomannem6585 5 жыл бұрын

Well-done sir. Thanks for sharing very good to understand everyone

@azmathalisyed9114 5 жыл бұрын

Great information,, good explanation.. 👌👌

@abhijitsarkar5946 5 жыл бұрын

Nice series. Get going. The numbers should be 630, 270 and the accuracy exactly 90%. This is the same as your original imbalance.

@tusharbhatnagar3146 4 жыл бұрын

Can you make video/tutorial on hyper parameter tuning in classification algorithms!! As it has been coming to many interviews also.

@neelpatel3844 4 жыл бұрын

Very informative, thank you.

@praveensingh1234 4 жыл бұрын

Very nice explain, Thanks a lot.

@SandeepSingh-tf7ni 5 жыл бұрын

Simplistic approach for Beginners, would really appreciate if you could do demo with dataset(1000 rows ) of 4-5 features, as well please explain Xgboost. Thanks in advance. Look forward to you response.

@umang8895 5 жыл бұрын

great video, easy to understand.

@vineetsansi 5 жыл бұрын

XGboost will take care of the weights by itself and we don't need to do any weight adjustment manually ... is that right?? Great videos .. thanks for sharing them .. I am sure you will get big number of followers very soon!! I am also applying XGBoost to the DataScience youtube channels that I am following and your channel seems to be getting heavier and heavier weights ;)

@aayushijain2160 4 жыл бұрын

Sir I have a doubt in this question that how to handle imbalanced data-set either by using right evaluation metrics or by these sampling techniques???Please let me know I'm very much confused...

@cinemascope8847 4 жыл бұрын

aayushi jain SMOTE can be used where we are increasing the minority data. Safest technique

@udanial 2 жыл бұрын

From which playlist this video is?

@satyaranjanbehera5492 5 жыл бұрын

good explanation..Thanks..

@prasanthkumar7328 5 жыл бұрын

while doing downsampling as mentioned we will be reducing the points to 100 so which points to be reduced or simply picking in random is also not a good practice so how could we select those 100 points.

@dr.bheemsainik4316 2 жыл бұрын

Sir, I have data with binary classification output variables. the ratio of classes is 7.5:2.5. Is this balanced data or unbalanced data?

@HarpreetKaur-mn4we 5 жыл бұрын

Very helpful video

@MsRAJDIP 5 жыл бұрын

Can u show the techniques of handling missing data excluding mean,median mode technique. I read that u can use regression or classification technique to find missing values but never seen implemented.

@shashankvashishtha9149 3 жыл бұрын

can u please explain the that 2 algorithms xgboost and adaboost?

@DatAcuity 3 жыл бұрын

I am just asking, So, if we use xgboost algorithm for classification problem we no need to bother about class imbalance. Am I right sir.

@gopalakrishna9510 4 жыл бұрын

i really happy with imbalanced and balanced dataset explaination.......

@sashpatra88 4 жыл бұрын

Krish : Can you put this in MACHINE LEARNING playlist? If I am not missing anything

@biswanandanpattanayak1938 4 жыл бұрын

how to handle missing data if data is 1tb or more? please explain

@manishshukla125 4 жыл бұрын

Thanks Sir, plz make a video for overfitting and underfitting

@Shylajakarthick 5 жыл бұрын

Thank you so much

@niketanjha 5 жыл бұрын

Really helpful 🙏

@moulidinavahi1498 4 жыл бұрын

How we can downsample data points ?

@harshays2873 4 жыл бұрын

sir suppose if i have less data to train my model at the time what i have to do?

@prithviraj25 4 жыл бұрын

Thankyou Sir

@NinjaAnkit 4 жыл бұрын

what i feel when see you videos explanation, your explanation like as when you communicating in english in your video its feels like you are communicating in regional language ..........thats why i understand more.........you explain most of the difficult terms in simple way. I love your explanation.

@NinjaAnkit 4 жыл бұрын

and also i remembered most of the concept in long time .

@NinjaAnkit 4 жыл бұрын

and i also like your videos which i watched.

@rahulmahajan6391 4 жыл бұрын

Can we do down sampling in credit card fraud detection dataset?

@surendranathify82 5 жыл бұрын

very useful . thanks. could you pls post video on PCA and LDA and about Regularization as well. thanks

@krishnaik06 5 жыл бұрын

Thanks, please check my playlist, video is already there for PCA

@mandarpawar27 4 жыл бұрын

Hi krish Plz upload vedios on interview questions

@kakarlanagajyothi4089 4 жыл бұрын

Small doubt missclassfication and imbalanced are same or different..

@kakarlanagajyothi4089 4 жыл бұрын

Pls answer me

@galisurendra6397 4 жыл бұрын

reply this question please

@gopalakrishna9510 4 жыл бұрын

can you explian with python codes ?

@karndeepsingh 4 жыл бұрын

how to deal with imbalance dataset when we have multiclass in target variable?

@MasterofPlay7 4 жыл бұрын

use other metrics such as F1 score instead of accuracy...

@kakarlanagajyothi4089 4 жыл бұрын

any videos for continuing these

@joyeetamallik5063 4 жыл бұрын

Can you share python code to implement these up sampling techniques. Is this concept is also applicable to NLP datasets?

@PhilippHusiA 4 жыл бұрын

If working with tf.keras, add following code to model: 1) from skearn.utils import class_weight 2) class_weights = class_weight.compute_class_weight('balanced',np.unique(y_train),y_train) 3) history = tf.keras.model.fit(x_train, y_train, batch_size=x, class_weight=class_weights)

@venkataraomannem6585 5 жыл бұрын

Sir can you please do this same as practically. Thank you sir

@sushedbubai 5 жыл бұрын

Waiting for more interview questions

@krishnaik06 5 жыл бұрын

You can find the complete playlist on the below youtube url kzfaq.info/sun/PLZoTAELRMXVPkl7oRvzyNnyj1HS4wt2K- I will be updating this with all the questions