机器学习测试算法的相关内容

[帮助文档] 机器学习线性支持向量机算法组件的配置及示例

支持向量机SVM（Support Vector Machine）是基于统计学习理论的一种机器学习方法，通过寻求结构风险最小化，提高学习机泛化能力，从而实现经验风险和置信范围最小化。本文介绍线性支持向量机算法组件的配置方法及使用示例。

机器学习测试笔记（21）——朴素贝叶斯算法

1.朴素贝叶斯概率统计概念1.1数学公式 P(B|A)· P(A) P(A|B) = —————————— ...

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机器学习测试笔记（10）——K邻近算法（下）

案例1：红酒分类上面我们采用make_blobs模拟数据来介绍K邻近算法，下面我们通过sklearn数据集来看一下K邻近算法的表现。 # 红酒案例 # 导入sklearn数据集 from sklearn import datasets def Sklean_wine(): #导入红酒数据集 wine...

机器学习测试笔记（10）——K邻近算法（上）

监督学习和非监督学习我们谈起机器学习经常会听到监督学习和非监督学习，它们的区别在哪里呢？监督学习是有标签的，而非监督学习是没有标签的。比如有一批酒，我们知道里面包括红酒和白酒，算法f可以用于鉴别某一个酒是否为红酒和白酒，这时候算法f就称作为监督学习，红酒、白酒即为标签。如果现在另有一批酒࿰...

数学建模国赛：python机器学习基础之训练集和测试集拆分、算法精确率评估

在实际训练中，经常会把训练数据进一步拆分成训练集和测试集这样有助于模型选取。想要数据集或者有不明白的请点赞关注后私信博主Sklearn中的train_test_spilt函数是交叉验证常用的函数，功能是从样本中随机地按比例选取训练集和测试集原数据如下：拆分后效果如下 ton代码如下from sk...

机器学习中的测试算法是什么呢？

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