XuesenYang's repositories
Multiclassification-FactorizationMachines
A Factorization Machines for Multiple Classification Tasks.
FNN_with_numpy
Implementation of feedforward neural network based on numpy
FOST
FOST is a general forecasting tool, which demonstrate our experience and advanced technology in practical forecasting domains, including temporal, spatial-temporal and hierarchical forecasting. Current general forecasting tools (Gluon-TS by amazon, Prophet by facebook etc.) can not process and model structural graph data, especially in spatial domains, also those tools suffer from tradeoff between usability and accuracy. To address these challenges, we design and develop FOST and aims to empower engineers and data scientists to build high-accuracy and easy-usability forecasting tools.
stylegan3
Official PyTorch implementation of StyleGAN3
Feature-rank-feature-selection
A noval feature selection method similar to pagerank method, and ultilized Bayesian optimization to search appropriate parameters
jMetalPy
A framework for single/multi-objective optimization with metaheuristics
LSTM-for-Time-Series-Forecasting-Pytorch
使用LSTM、GRU、BPNN进行时间序列预测。Using LSTM\GRU\BPNN for time series forecasting. (Pytorch Edition)
Graph-clustering-with-ant-colony-optimization-for-feature-selection
A graph clustering method with ant colony optimization for feature selection
yolov3-channel-and-layer-pruning
yolov3 yolov4 channel and layer pruning, Knowledge Distillation 层剪枝，通道剪枝，知识蒸馏
Financial-risk-control-fraud-detection
Some common financial risk control models
Python-100-Days
Python - 100天从新手到大师
machine_learning
机器学习练习
TensorFLow-Learning
B站上炼数成金的公开课笔记
Machine-Learning-Decision-Tree
Machine Learning Decision Tree
IsolationForest-feature-ranking
using a single IsolationForest method to rank features
MAD-GANs
Applied generative adversarial networks (GANs) to do anomaly detection for time series data
Curious-feature-selection
Implementation of curious-feature-selection
competitive-swarm-optimizer-feature-selection-CSOFS
Implementation of a competitive swarm optimizer (CSO) for feature selction
Q-learning-feature-selection
A simple reinforcement learning for feature selection
xgbfir
XGBoost Feature Interactions Reshaped
Improved-Decision-Tree-Based-on-Feature-Ranking
An improved decision tree classifier, in which the feature ranking threshold is used to replace Gini coefficient or information gain rate, as a criterion for judging whether a feature can be used as a tree node.
KNN-classification-with-python
Layered sampling 10 fold cross validation＋30runtimes＋Multiple assessment