Alexey Chervonenkis

(5 articles)

1970

Bias-Variance Trade-off

In ML, achieving optimal model performance involves balancing bias and variance to minimize overall error.

Generality: 818

1971

VC
Dimension
Vapnik-Chervonenkis

Measure of the capacity of a statistical classification algorithm, quantifying how complex the model is in terms of its ability to fit varied sets of data.

Generality: 806

1974

Empirical Risk Minimization

A foundational principle in statistics and ML (Machine Learning), focused on minimizing the average of the loss function over a sample dataset.

Generality: 814

1992

Bias-Variance Dilemma

Fundamental problem in supervised ML that involves a trade-off between a model’s ability to minimize error due to bias and error due to variance.

Generality: 893

1995

Margin

In the context of AI, particularly in Support Vector Machines (SVM), margin refers to the separation between data points of different classes, signifying the distance between the decision boundary and the closest data points of the classes.