bias variance tradeoff underfitting

Dov Chriqui answered on June 20, 2022 Popularity 10/10 Helpfulness 2/10

answer bias variance tradeoff underfitting

related bias variance tradeoff

related bias variance tradeoff and overfitting

bias variance tradeoff underfitting

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Underfitting happens when a model unable to capture the underlying 
pattern of the data. 
These models usually have high bias and low variance

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Contributed on Jun 20 2022

Dov Chriqui

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bias variance tradeoff

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- Overfitting : 
    - Model also memorises / trains on noise that resides within training data. 
    - Model performs well when evaluating on training data but does not perform well on unseen data
    - High variance is responsible for this error because of also capturing noise.
    - Diagnosis: cross-val prediction on test set has high error than prediction on train set
    - Possible remedy : Decrease model complexity, gather more data, 
- Underfitting :
    - Model is too simple to catch the pattern, model is not good enough to capture the underlying pattern.
    - Model is bad on both training and unseen data
    - Model is not flexibple enough to approximate the prediction values
    - High bias is responsible for this error
    - Diagnosis: cross-val prediction on train and test set are roughly equal but have very high errors that is undesirable
    - Possible remedy : Increase model complexity, gather more features, 
- Bias-Variance trade-off :
    - Generalization error = bias^2 + variance + irreducable error (noise)
    - bias = error term that tells how on average real value is different from predicted value
    - variance = error term that tells how predicted value varies over different training sets
    - When model complexity increases, variance increases and bias decreases
    - When model complexity decreases, variance decreases and bias increases
    - The sweet spot is the minimised generalization error, which gives the optimised model

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Contributed on Jan 02 2024

Innocent Iguana

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bias variance tradeoff and overfitting

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Overfitting happens when our model captures the noise along with the 
underlying pattern in data.
Low bias High Variance

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Contributed on Jun 20 2022

Dov Chriqui

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bias variance tradeoff underfitting

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