ja4-platform

Files

Jacquin Antoine 7894d39f1c feat(ml): replace logistic regression with MLP fusion and KS drift with ADWIN online learning

Replace the LogisticRegression meta-learner with a PyTorch MetaFusionMLP
(Linear(3,16)->BN->ReLU->Dropout->Linear(16,1)->Sigmoid) for non-linear
fusion of EIF, NF, and XGBoost scores. Replace KS-test + quantile digest
drift detection with ADWIN (adaptive sliding window, Hoeffding bound).
Replace weekly XGBoost batch retraining with River HoeffdingAdaptiveTree
for incremental online learning (learn_one per cycle). Update all thesis
documentation sections (2.4.2c, 2.4.3, 3.8, discussion, conclusion).

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

2026-04-13 16:32:34 +02:00

database

docs: mise à jour complète — 7/8 techniques, 85 features, 12 modules

2026-04-10 01:31:20 +02:00

services

feat(ml): replace Autoencoder with RealNVP Normalizing Flow and add SessionTransformer embeddings

2026-04-13 15:11:21 +02:00

shared

docs: réécriture complète de la documentation des services en français

2026-04-09 22:04:58 +02:00

thesis

feat(ml): replace logistic regression with MLP fusion and KS drift with ADWIN online learning