python分别实现基于神经网络、线性回归、SVM方法预测学生成绩源码+数据集.zip

[{"title":"（ 15 个子文件 12.19MB ） python分别实现基于神经网络、线性回归、SVM方法预测学生成绩源码+数据集.zip","children":[{"title":"python分别实现基于神经网络、线性回归、SVM方法预测学生成绩源码+数据集","children":[{"title":"data_convert.py <span style='color:#111;'> 6.33KB </span>","children":null,"spread":false},{"title":"data","children":[{"title":"catalog.npy <span style='color:#111;'> 52.90MB </span>","children":null,"spread":false},{"title":"borrow.npy <span style='color:#111;'> 509.36KB </span>","children":null,"spread":false},{"title":"access.npy <span style='color:#111;'> 1.86MB </span>","children":null,"spread":false},{"title":"consumption.npy <span style='color:#111;'> 28.83MB </span>","children":null,"spread":false},{"title":"score.npy <span style='color:#111;'> 37.91KB </span>","children":null,"spread":false},{"title":"catalog.txt <span style='color:#111;'> 17.08MB </span>","children":null,"spread":false},{"title":"access.txt <span style='color:#111;'> 1.09MB </span>","children":null,"spread":false},{"title":"borrow.txt <span style='color:#111;'> 314.90KB </span>","children":null,"spread":false},{"title":"score.txt <span style='color:#111;'> 16.73KB </span>","children":null,"spread":false},{"title":"consumption.txt <span style='color:#111;'> 12.18MB </span>","children":null,"spread":false}],"spread":true},{"title":"项目说明.md <span style='color:#111;'> 617B </span>","children":null,"spread":false},{"title":"worker.py <span style='color:#111;'> 3.91KB </span>","children":null,"spread":false},{"title":"temp.py <span style='color:#111;'> 1.21KB </span>","children":null,"spread":false},{"title":"utils","children":[{"title":"__init__.py <span style='color:#111;'> 0B </span>","children":null,"spread":false}],"spread":true}],"spread":true}],"spread":true}]