note

過学習（Overfitting）： AI システムの開発における本質的な問題

以前、集合学習や、交差検証に関する記事、また機械学習のECへの応用に関する記事等で、繰り返し、AIシステムにおけるモデルのロバストネスを高め、「過学習（Overfitting）」をいかに防いでいくかが大事であると述べました。 今回は、そもそもその「過 ...
GitHub

Eliminating Catastrophic Overfitting Via Abnormal Adversarial Examples Regularization

Single-step adversarial training (SSAT) has demonstrated the potential to achieve both efficiency and robustness. However, SSAT suffers from catastrophic overfitting (CO), a phenomenon that leads to a ...
Europe PMC

Empirical Study of Overfitting in Deep Learning for Predicting Breast Cancer Metastasis.

Overfitting may affect the accuracy of predicting future data because of weakened generalization. In this research, we used an electronic health records (EHR) dataset concerning breast cancer ...
IEEE

Overfitting Problem of ANN- and VSTF-Based Nonlinear Equalizers Trained on Repeated Random ...

Abstract: In this paper, we investigated the overfitting characteristics of nonlinear equalizers based on an artificial neural network (ANN) and the Volterra series transfer function (VSTF), which ...
Analytics India Magazine

5 methods that will not let your neural network model overfit

Through this post we will discuss about overfitting and methods to use to prevent the overfitting of a neural network. Everyone in the data science field is starving for a modelling procedure that can ...