ztqakita's Blog
Posts
Introduction
Algorithms
Complexity & Divide and Conquer
Dynamic Programming
Greedy & Back-track & Branch and Bound
Compiler
Lexcial Analysis & Parsing
Semantic Analysis & Runtime Environment
Syntax-directed Translation
Computational Neuroscience
Ionic Currents
Neuroscience Basic Knowledge
Database System
Database System Lecture Note 1
Database System Lecture Note 2
Database System Lecture Note 3
Database System Lecture Note 4
DL
Convolutional Neural Network
Introduction to Deep Learning
Optimization for Deep Learning
Recursive Neural Network
Self-attention
Transformer
Life Learning
Architectures of neuronal circuits
how to model
Lecture James McClleland
Lecture Yao Xin
ML
Basic Concepts
Classification
Decision Tree
KNN
Perceptron
SOM
Support Vector Machines
Operating System
CPU Scheduling
File System
Introduction & OS Structure
Mass-Storage Structure & I/O System
Memory Management
Process & Threads
Process Synchronization
Paper Reading
Continuous-attractor Neural Network
Few-Shot Class-Incremental Learning
Integrated understanding system
Push-pull feedback
reservoir decision making network
Task representations in neural networks
Brandon Zhang
January 27, 2021
Perceptron
原理
参考:
统计学习方法|感知机原理剖析及实现
输入:实例的特征向量
输出:实例的类别(二分类)
模型类别:判别模型
学习策略:基于误分类的损失函数,利用梯度下降法对损失函数进行极小化,求得感知机模型
Improve this page
Prev
Basic Concepts
Next
Database System Lecture Note 4
Table of Contents