搜索资源列表
regress-221
- Test that direct eval calls handle the case where eval has been deleted correctly.
regress-208496-001
- Testing with (f) inside the definition of function f().
regress-1175390
- production Member Expression for Linux v2.13.6.
regress-1114040
- Left Hand Side Expression for Linux v2.13.6.
regress-1182832
- generate a runtime error for Linux v2.13.6.
regress-220
- Ensure that compiling a declaration of a function does not crash.
regress-137
- base is now HeapNumber with valid Smi value.
regress-674753
- Returns the difference between local time and UTC time in minutes.
regress
- many regression functions for different regression techniques
SVM-Regress
- 基于SVM(支持向量机)的回归算法,很好用-Based on SVM (SVM) regression algorithm, very good use
statistical-analysis
- 随机模拟和统计分析 max,min - 最大,最小值 sum - 求和 mean - 均值 std - 标准差 sort - 排序(升序) sortrows - 按某一列排序(升序) rand - [0,1]区间均匀分布随机数 randn - 标准正态分布随机数 randperm - 1...n 随机排列 regress - 线性回归 classify - 统计聚类 *trim - 坏数据祛除 *specrnd -
regress-137
- base is now HeapNumber with valid Smi value.
regress-674753
- Returns the difference between local time and UTC time in minutes.
RFR
- 好用的随机森林回归(RFR),也可用与分类。基于以编译的mex84,可实现bias-correction。回归预测精度较高-applicable random forrest regression,can also be used for classification。Regress with bias-correction 。can achieve high accuracy
cjgl_v5.0.1
- 提供8种权限用户:校长室(可查询所有学生成绩信息),班主任(可录入、查询所任班级的所有学生成绩信息),任课老师(可录入、查询所任班级课程的所有学生成绩信息),学生、学生家长(可查询本学生的成绩信息),管理员(最高权限),年级组长(年级中的管理员权限),督察人员(专门针对学生评价系统内容的用户类型)。老师可在网络中录入、修改学生成绩,老师、学生、学生家长登录系统,可查询某一个或多个班的成绩情况,自动排名,自动生成平均分、最高分、最低分;同时可比较多次考试中某个学生的一门或多门程成绩情况(可生成柱状
cixingtaosuo
- 基于QT的磁性套索工具实现,在图上选择想要的区域,闭合以后可以裁剪出来,选则的边错误可以回退。-Implementation based on QT magnetic lasso tool and the desired area on the map. After the closure can be cut out, selection errors in edge can regress.
regress
- 一个xgboost实现的回归模型预测,数据集来源于kaggle的taxi竞赛(Regression model prediction based on a xgboost implementation)
小波神经网络
- 神经网络做回归预测,3层小波包结合在一起做预测(network regress prediction)
GPR-O-master
- github上找到的高斯过程回归的一个例子。(An example of the Gauss process regress found on GitHub.)