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c-machine-learning's Introduction

山东大学(威海)数学与统计学院2018级数据科学与人工智能实验班

暑假科研实训项目

指导教师:郭亮

项目成员:小高、小许、小闫、小叶、小E

C machine learning algorithm

目录:

  • 环境配置
    • 百度AI Studio介绍
    • 百度AI Studio配置
    • 百度AI Studio案例运行
  • 公共函数
    • 读取csv文件数据
    • 数据K折交叉验证
    • 数据标准化
    • 计算算法结果
    • 验证算法结果
  • 算法详解
    • Simple Linear Regression
    • Multivariate Linear Regression
    • Logistic Regression
    • Perceptron
    • Classifification and Regression Trees
    • Naive Bayes
    • $k$-Nearest Neighbors
    • Learning Vector Quantization
    • Support Vector Machine
    • Backpropagation
    • Bootstrap Aggregation
    • Random Forest
    • Stacked Generalization
  • 简易C语言教程

百度AI Studio链接:https://aistudio.baidu.com/aistudio/projectdetail/2309566

Github: https://github.com/Gao-Jianxiong-SDUWH/C-machine-learning

知乎专栏:https://www.zhihu.com/column/c_1296572278004940800

B站视频讲解:https://www.bilibili.com/video/BV1st4y1v72S/(未更新)

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c-machine-learning's Issues

coefficients_sgd函数中w的梯度更新公式

void coefficients_sgd(double ** dataset, int col, double *coef, double l_rate, int n_epoch, int train_size) { int i; for (i = 0; i < n_epoch; i++) { int j = 0;//±éÀúÿһÐÐ for (j = 0; j < train_size; j++) { double yhat = predict(col,dataset[j], coef); double err = dataset[j][col - 1] - yhat; coef[0] += l_rate * err * yhat * (1 - yhat); int k; for (k = 0; k < col - 1; k++) { coef[k + 1] += l_rate * err * yhat * (1 - yhat) * dataset[j][k]; } } } for (i = 0; i < col; i++) { //printf("coef[%d]=%f\n",i, coef[i]); } }

coef[k + 1] += l_rate * err * yhat * (1 - yhat) * dataset[j][k]
上面的梯度更新公式式改进的?

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