[20180324]_SVM

Directory: Mathimatics-Numerical algorithms
Plat: Python
Size: 1456KB
Description:   The combination of SVM algorithm in machine learning and artificial intelligence learning is the only way to machine learning and artificial intelligence learning and the best learning material for beginners.

File list:
[20180324]_SVM, 0 , 2019-10-09
[20180324]_SVM\.ipynb_checkpoints, 0 , 2019-10-09
[20180324]_SVM\.ipynb_checkpoints\01_案例一：鸢尾花数据SVM分类-checkpoint.ipynb, 87096 , 2018-03-24
[20180324]_SVM\.ipynb_checkpoints\05_案例五：异常值检测(OneClassSVM)-checkpoint.ipynb, 47657 , 2018-03-24
[20180324]_SVM\.ipynb_checkpoints\07_综合案例一：手写数字识别-checkpoint.ipynb, 30448 , 2018-03-24
[20180324]_SVM\.ipynb_checkpoints\09_综合案例三：使用SVM预测波士顿房价-checkpoint.ipynb, 4858 , 2018-03-24
[20180324]_SVM\.ipynb_checkpoints\10_综合案例四：分类算法比较-checkpoint.ipynb, 5893 , 2018-03-24
[20180324]_SVM\.ipynb_checkpoints\fz03_拉格朗日乘子法(帮助理解)-checkpoint.ipynb, 2470 , 2018-03-20
[20180324]_SVM\01_案例一：鸢尾花数据SVM分类.ipynb, 68576 , 2018-03-24
[20180324]_SVM\02_案例二：鸢尾花数据不同分类器效果比较.ipynb, 237906 , 2018-01-21
[20180324]_SVM\03_案例三：不同SVM核函数效果比较.ipynb, 257874 , 2018-01-21
[20180324]_SVM\04_案例四：不同SVM惩罚参数C值不同效果比较.ipynb, 195808 , 2018-01-21
[20180324]_SVM\05_案例五：异常值检测(OneClassSVM).ipynb, 47657 , 2018-03-24
[20180324]_SVM\06_案例六：SVM多目标属性分类问题(多标签分类的时候讲过).ipynb, 228660 , 2018-02-06
[20180324]_SVM\07_综合案例一：手写数字识别.ipynb, 30448 , 2018-03-24
[20180324]_SVM\08_综合案例二：自定义SVM内部核函数.ipynb, 38951 , 2018-01-21
[20180324]_SVM\09_综合案例三：使用SVM预测波士顿房价.ipynb, 116495 , 2018-03-24
[20180324]_SVM\10_综合案例四：分类算法比较.ipynb, 5893 , 2018-03-24
[20180324]_SVM\cs.png, 390331 , 2018-03-24
[20180324]_SVM\datas, 0 , 2019-10-09
[20180324]_SVM\datas\boston_housing.data, 49081 , 2018-01-08
[20180324]_SVM\datas\iris.data, 4551 , 2018-01-08
[20180324]_SVM\fz01_梯度下降法：一维和二维图像.ipynb, 120034 , 2018-01-30
[20180324]_SVM\fz02_梯度下降法：求解最优解最优解.ipynb, 9601 , 2018-01-30
[20180324]_SVM\fz03_拉格朗日乘子法(帮助理解).ipynb, 2470 , 2018-03-20