Definition Of Bias And Variance In Machine Learning- Interview Question

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Hello guys,
Please don't get confused.
For Training data :-
Good accuracy --> low bias
Bad accuracy --> high bias
For Testing data:-
Good accuracy --> low variance
Bad accuracy --> high variance

sidharth

3:14 it should be low bias when model is performing well

rafibasha

One can only understand these conpects better while implementing the same into their respective work. Your videos are worth watching and I urge people to practice such concepts into their respective projects to get clear idea.

vishaldas

thanks kirsh for this video model 1(example for over fitting) and model 2(example for under fitting) finally model 3 is perfect model to use.

saitarun

Finally i broke blackbox of Bias & Variance.. Thank you Krish 🙏🙏

TeluguBlockChain

3:14 low bias high and varience is just a error respect to training dataset and test (Validation) data model perform well, it means low error.

suriyaprakashkk

Krish i think you mentioned wrongly in case of bias at 3.20min.... when model is performing well on training data it means error is low and this is low bias case but you said when model is performing well on training data its high bias

high bias means high training error

karrmanbhatia

Sir, could you make videos on algebra and calculas, and how to code these in python to use these effectively in machine learning.

sumanreddy

Low bias/low variance :When model is performing well on both train and test

High bias :When model is neither performing good at training/test

High variance :Performing well on train but not on test

rafibasha

I think you explaining in white board the traditional way is far far better than digital board..

JaiRudraNath

Thank you for this clear presentation. I have a question about low variance variable, how to find low variance variable (threshold)
, why and when we should remove this variables ?

ikram_

In model 1 the accuracy training is high still u r saying low bias u said high train accuracy means high bias

AmanKumarSharma-deft

Sir agar m hp Pavillion aero 13 laptop leta hu to ye acha rhe ga long term k liy kyu k models to Google colab m train ho jay gy ap ka experience ka khehta h?

ParasProgramming

To be corrected....definition of high and low bias in training data set

ManojKumar-gedj

your explanation is wrong at 3:14. A model performing well on training dataset will have high training accuracy, low error/Bias. Bias is the measurement of error. Model fit (Y_hat) against the existing training dataset (x). The delta between (y_hat) and training points is the Bias.

VijayBhaskarSingh

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