VFDT-split-time-prediction
Adaptation algorithm
An implementation of split-time prediction algorithms for adapting to changing data distributions in various domains.
0 stars
0 watching
1 forks
Language: Java
last commit: over 6 years ago
Linked from 1 awesome list
Related projects:
Repository | Description | Stars |
---|---|---|
vlosing/vfdt-split-time-prediction | An implementation of split-time prediction algorithms using the Hoeffding-Tree data structure in Java | 0 |
younghjung/onlinemlrboostingwithvfdt | An implementation of online multi-label ranking boosting using VFDT as weak learners | 4 |
predict-idlab/tsflex | A toolkit for flexible time series processing and feature extraction. | 402 |
rjt1990/pydata2016-sanfrancisco | An analysis of time series methods using PyFlux library and incorporating NFL prediction model. | 23 |
wasidennis/adaptsegnet | This project implements a deep learning-based approach to adapt semantic segmentation models from one domain to another. | 849 |
florentavellaneda/inferdt | This C++ project provides an implementation of decision tree algorithms for classification tasks | 7 |
rgavaska/fast-adaptive-bilateral-filtering | An implementation of an adaptive image filtering algorithm with local windowed minima and maxima detection | 77 |
springdaisy/gbdt | An implementation of Gradient Boosted Decision Trees with sparse output for high-dimensional data | 0 |
naoto0804/cross-domain-detection | Develops object detection algorithms to adapt to new domains with limited supervision | 422 |
mingruiliu-ml-lab/episode_plusplus | An algorithm for Federated Learning that handles client subsampling and data heterogeneity with unbounded smoothness | 0 |
predict-idlab/gendis | An algorithm to discover small, discriminative patterns in time series data for classification tasks | 103 |
ericzhao28/multidistributionlearning | This project provides an implementation of On-Demand Sampling: Learning Optimally from Multiple Distributions, a method for learning from multiple distributions in federated learning. | 8 |
wannesm/dtaidistance | A library that implements a fast and efficient distance measure for time series data | 1,089 |
baowenxuan/atp | An implementation of adaptive test-time personalization for federated learning in deep neural networks. | 16 |
jiangoforit/yellowfin_pytorch | An optimizer that automatically tunes momentum and learning rate using local quadratic approximation. | 287 |