smote的matlab代码-machine_learning:基本机器学习

上传者: 38628552 | 上传时间: 2022-05-09 20:20:32 | 文件大小: 4.51MB | 文件类型: ZIP
smote的matlab代码介绍 该项目实现了经典的机器学习算法(ML)。 这个项目的动机包括: 帮助机器学习大一新生对这个领域的基本算法和模型有更好更深入的理解。 在 ML 领域提供现实生活和商业执行方法。 由于这种情况,我的数学理论和编码能力保持新鲜。 概述 1.调频 1.1 fast_fm 展示如何使用“fast_fm”包对数据集进行分类。 1.2 fm_rewrite 遵循FM的理论,我们自己编写python脚本。 1.3 使用者: pip install fm_easy_run 。 2.xgboost 2.1 xgboost 展示如何使用“xgboost”包对数据集进行分类。 2.2 网格搜索 展示如何使用“gridsearch”包来选择“xgboost”算法的最佳参数。 3.N-gram 用 n-gram 代替朴素贝叶斯解决的面试问题。 4.Svd @博尔格: 4.1 linalg中的矩阵分解 4.2 矩阵分解与 RSVD 5.协同过滤推荐系统 @博尔格: 5.1 项目基础 5.2 用户基础 6.语义识别 @博尔格: 6.1 解霸流程 6.2 Tf-Idf 6.3 Bp 神

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