<?xml version="1.0" encoding="utf-8" ?><rss version="2.0"><channel><title><![CDATA[Ninina1992的博客]]></title><description><![CDATA[]]></description><link>https://blog.youkuaiyun.com/Ninina1992</link><language>zh-cn</language><generator>https://blog.youkuaiyun.com/</generator><copyright><![CDATA[Copyright &copy; Ninina1992]]></copyright><item><title><![CDATA[Python实现个性化推荐二]]></title><link>https://blog.youkuaiyun.com/Ninina1992/article/details/101924708</link><guid>https://blog.youkuaiyun.com/Ninina1992/article/details/101924708</guid><author>Ninina1992</author><pubDate>Fri, 12 Oct 2018 16:57:00 +0800</pubDate><description><![CDATA[基于内容的推荐引擎是怎么工作的

基于内容的推荐系统，正如你的朋友和同事预期的那样，会考虑商品的实际属性，比如商品描述，商品名，价格等等。如果你以前从没接触过推荐系统，然后现在有人拿枪指着你的...]]></description><category></category></item><item><title><![CDATA[Python实现个性化推荐一]]></title><link>https://blog.youkuaiyun.com/Ninina1992/article/details/101924707</link><guid>https://blog.youkuaiyun.com/Ninina1992/article/details/101924707</guid><author>Ninina1992</author><pubDate>Fri, 12 Oct 2018 16:56:00 +0800</pubDate><description><![CDATA[　　现如今，网站用推荐系统为你提供个性化的体验，告诉你买啥，吃啥甚至你应该和谁交朋友。尽管每个人口味不同，但大体都适用这个套路。人们倾向于喜欢那些与自己喜欢的其他东西相似的东西，也倾向于与自己身边的人有相似的口味。推荐系统就尝试捕捉这一规律来帮助预测你也可能喜欢的其他东西。

　　为帮用户...]]></description><category></category></item><item><title><![CDATA[matlab 常用集合相关的函数]]></title><link>https://blog.youkuaiyun.com/Ninina1992/article/details/101924702</link><guid>https://blog.youkuaiyun.com/Ninina1992/article/details/101924702</guid><author>Ninina1992</author><pubDate>Fri, 12 Oct 2018 16:54:00 +0800</pubDate><description><![CDATA[Matlab常用的集合相关的函数如下：
union(A,B) %求集合A和集合B的并集
intersect(A,B)   %求集合A和集合B的交集
setdiff(A,B) %求集合A和集合B的差集，即A-B；亦可看成求取集合B关于全集A的补集。
unique(A)...]]></description><category></category></item><item><title><![CDATA[MATLAB画图符号标注]]></title><link>https://blog.youkuaiyun.com/Ninina1992/article/details/101924706</link><guid>https://blog.youkuaiyun.com/Ninina1992/article/details/101924706</guid><author>Ninina1992</author><pubDate>Fri, 12 Oct 2018 16:52:00 +0800</pubDate><description><![CDATA[线型
            
            
            说明
            
            
           ...]]></description><category></category></item><item><title><![CDATA[感知机(perceptron)]]></title><link>https://blog.youkuaiyun.com/Ninina1992/article/details/101924700</link><guid>https://blog.youkuaiyun.com/Ninina1992/article/details/101924700</guid><author>Ninina1992</author><pubDate>Fri, 12 Oct 2018 16:51:00 +0800</pubDate><description><![CDATA[...]]></description><category></category></item><item><title><![CDATA[朴素贝叶斯概率方法]]></title><link>https://blog.youkuaiyun.com/Ninina1992/article/details/101924703</link><guid>https://blog.youkuaiyun.com/Ninina1992/article/details/101924703</guid><author>Ninina1992</author><pubDate>Fri, 12 Oct 2018 16:50:00 +0800</pubDate><description><![CDATA[...]]></description><category></category></item><item><title><![CDATA[EM算法]]></title><link>https://blog.youkuaiyun.com/Ninina1992/article/details/101924698</link><guid>https://blog.youkuaiyun.com/Ninina1992/article/details/101924698</guid><author>Ninina1992</author><pubDate>Fri, 12 Oct 2018 16:49:00 +0800</pubDate><description><![CDATA[...]]></description><category></category></item><item><title><![CDATA[逻辑回归与最大熵模型]]></title><link>https://blog.youkuaiyun.com/Ninina1992/article/details/101924701</link><guid>https://blog.youkuaiyun.com/Ninina1992/article/details/101924701</guid><author>Ninina1992</author><pubDate>Fri, 12 Oct 2018 16:48:00 +0800</pubDate><description><![CDATA[...]]></description><category></category></item><item><title><![CDATA[提升方法-AdaBoost]]></title><link>https://blog.youkuaiyun.com/Ninina1992/article/details/101924699</link><guid>https://blog.youkuaiyun.com/Ninina1992/article/details/101924699</guid><author>Ninina1992</author><pubDate>Fri, 12 Oct 2018 16:47:00 +0800</pubDate><description><![CDATA[提升方法通过改变训练样本的权重，学习多个分类器(弱分类器/基分类器)并将这些分类器进行线性组合，提高分类的性能。AdaBoost算法的特点是不改变所给的训练数据，而不断改变训练数据权值的分布，使得训...]]></description><category></category></item><item><title><![CDATA[隐马尔可夫模型HMM]]></title><link>https://blog.youkuaiyun.com/Ninina1992/article/details/101924697</link><guid>https://blog.youkuaiyun.com/Ninina1992/article/details/101924697</guid><author>Ninina1992</author><pubDate>Fri, 12 Oct 2018 16:45:00 +0800</pubDate><description><![CDATA[https://img-blog.youkuaiyun.com/20180714161442742?watermark/2/text/aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3UwMTMxODUzNDk=/font/5a6L5L2T/fontsize/400/fill/I0JBQkFCMA==/dissolve/70


转载于:https://www.cnblogs.com/Ac...]]></description><category></category></item><item><title><![CDATA[条件随机场CRF]]></title><link>https://blog.youkuaiyun.com/Ninina1992/article/details/101924695</link><guid>https://blog.youkuaiyun.com/Ninina1992/article/details/101924695</guid><author>Ninina1992</author><pubDate>Fri, 12 Oct 2018 16:44:00 +0800</pubDate><description><![CDATA[条件随机场(CRF)是给定一组输入随机变量X的条件下另一组输出随机变量Y的条件概率分布模型，其特点是假设输出随机变量构成马尔科夫随机场。实际上是定义在时序数据上的对数线性模型。条件随机场属于判别模型...]]></description><category></category></item><item><title><![CDATA[判别模型和生成模型的区分]]></title><link>https://blog.youkuaiyun.com/Ninina1992/article/details/101924693</link><guid>https://blog.youkuaiyun.com/Ninina1992/article/details/101924693</guid><author>Ninina1992</author><pubDate>Fri, 12 Oct 2018 16:43:00 +0800</pubDate><description><![CDATA[判别模型：感知机，KNN，决策树，Logit回归与最大熵，SVM，Boosting，条件随机场；生成模型：朴素贝叶斯，隐马尔可夫模型；区分分类和标注：分类问题中可能的预测结果是二类或多类；而标注问题...]]></description><category></category></item><item><title><![CDATA[K-Means和FCM聚类]]></title><link>https://blog.youkuaiyun.com/Ninina1992/article/details/101924696</link><guid>https://blog.youkuaiyun.com/Ninina1992/article/details/101924696</guid><author>Ninina1992</author><pubDate>Fri, 12 Oct 2018 16:41:00 +0800</pubDate><description><![CDATA[K均值聚类是基于原型的、划分的聚类方法。聚类数K由用户指定，初始的K个聚类中心随机选取，然后将每个点分派到最近的聚类中心，形成K个簇，接下来重新计算每个簇的聚类中心，重复上一步，直到簇不发生变化或达...]]></description><category></category></item><item><title><![CDATA[SVM知识点]]></title><link>https://blog.youkuaiyun.com/Ninina1992/article/details/101924691</link><guid>https://blog.youkuaiyun.com/Ninina1992/article/details/101924691</guid><author>Ninina1992</author><pubDate>Fri, 12 Oct 2018 16:38:00 +0800</pubDate><description><![CDATA[SVM(Support Vector Machine)，支持向量机，有监督学习模型，一种分类模型。在特征空间（输入空间为欧式空间或离散集合，特征空间为欧式空间或希尔伯特空间）中寻找间隔最大化的分离超...]]></description><category></category></item><item><title><![CDATA[解释机器学习中的方差和偏差]]></title><link>https://blog.youkuaiyun.com/Ninina1992/article/details/101924689</link><guid>https://blog.youkuaiyun.com/Ninina1992/article/details/101924689</guid><author>Ninina1992</author><pubDate>Fri, 12 Oct 2018 16:38:00 +0800</pubDate><description><![CDATA[偏差反映的是模型在样本上的输出和真实值之间的误差(偏离程度)，即模型本身的准确度，拟合能力；解决：使用更复杂的模型，使用更多的特征。方差反映的是模型每一次随数据集的变动造成的输出结果与模型输出期望之...]]></description><category></category></item><item><title><![CDATA[Regularization method for machine learning]]></title><link>https://blog.youkuaiyun.com/Ninina1992/article/details/101924687</link><guid>https://blog.youkuaiyun.com/Ninina1992/article/details/101924687</guid><author>Ninina1992</author><pubDate>Fri, 12 Oct 2018 16:36:00 +0800</pubDate><description><![CDATA[Regularization method(正则化方法)

Outline

Overview of Regularization

L0 regularizat...]]></description><category></category></item><item><title><![CDATA[Gated Recurrent Unit (GRU)]]></title><link>https://blog.youkuaiyun.com/Ninina1992/article/details/101924694</link><guid>https://blog.youkuaiyun.com/Ninina1992/article/details/101924694</guid><author>Ninina1992</author><pubDate>Fri, 12 Oct 2018 16:35:00 +0800</pubDate><description><![CDATA[Gated Recurrent Unit (GRU) 

Outline     

         Ba...]]></description><category></category></item><item><title><![CDATA[Long Short-Term Memory (LSTM)]]></title><link>https://blog.youkuaiyun.com/Ninina1992/article/details/101924684</link><guid>https://blog.youkuaiyun.com/Ninina1992/article/details/101924684</guid><author>Ninina1992</author><pubDate>Fri, 12 Oct 2018 16:33:00 +0800</pubDate><description><![CDATA[Long Short-Term Memory (LSTM)

Outline        

        Back...]]></description><category></category></item><item><title><![CDATA[GBDT && XGBOOST]]></title><link>https://blog.youkuaiyun.com/Ninina1992/article/details/101924692</link><guid>https://blog.youkuaiyun.com/Ninina1992/article/details/101924692</guid><author>Ninina1992</author><pubDate>Fri, 12 Oct 2018 16:31:00 +0800</pubDate><description><![CDATA[GBDT &amp;&amp; XGBOOST 

            

Outline

   ...]]></description><category></category></item><item><title><![CDATA[[LeetCode] Remove Invalid Parentheses 移除非法括号]]></title><link>https://blog.youkuaiyun.com/Ninina1992/article/details/101924690</link><guid>https://blog.youkuaiyun.com/Ninina1992/article/details/101924690</guid><author>Ninina1992</author><pubDate>Fri, 12 Oct 2018 16:29:00 +0800</pubDate><description><![CDATA[[LeetCode] Remove Invalid Parentheses 移除非法括号

删除最小数量的无效括号，使得输入的字符串有效，返回所有可能的结果。

说明:输入可能包含了除...]]></description><category></category></item></channel></rss>