Paper Code：A Self-adaptive Weighted Differential Evolution Approach for Large-scale Feature Selection

wangxb

Last update: Dec 8, 2022

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Deep Learning SaWDE

Overview

1. SaWDE.m is the main function

2. DataPartition.m is used to randomly partition the original data into training sets and test sets with a ratio of 7 : 3.

3. CSGSTest.m is used to test the performance of each strategy.

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Owner

wangxb

Data Mining & Machine Learning : ) Knowledge in Data

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An Efficient Training Approach for Very Large Scale Face Recognition or F²C for simplicity.

Fast Face Classification (F²C) This is the code of our paper An Efficient Training Approach for Very Large Scale Face Recognition or F²C for simplicit

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PyTorch Implementation for AAAI'21 "Do Response Selection Models Really Know What's Next? Utterance Manipulation Strategies for Multi-turn Response Selection"

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The source code for the Cutoff data augmentation approach proposed in this paper: "A Simple but Tough-to-Beat Data Augmentation Approach for Natural Language Understanding and Generation".

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Paper Code：A Self-adaptive Weighted Differential Evolution Approach for Large-scale Feature Selection

Related tags

Overview

1. SaWDE.m is the main function

2. DataPartition.m is used to randomly partition the original data into training sets and test sets with a ratio of 7 : 3.

3. CSGSTest.m is used to test the performance of each strategy.

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