上一页 1 ··· 149 150 151 152 153 154 155 156 157 ··· 274 下一页
摘要: Given a binary search tree (BST), find the lowest common ancestor (LCA) of two given nodes in the BST. According to the definition of LCA on Wikipedia 阅读全文
posted @ 2018-05-29 22:57 bonelee 阅读(189) 评论(0) 推荐(0)
摘要: Given a non-empty array of digits representing a non-negative integer, plus one to the integer. The digits are stored such that the most significant d 阅读全文
posted @ 2018-05-28 23:40 bonelee 阅读(214) 评论(0) 推荐(0)
摘要: 手写汉字笔迹识别模型: 第一名用的是googleNet,准确率97.3% def GoogleLeNetSlim(x, num_classes, keep_prob=0.5): with tf.variable_scope('main'): t = slim.conv2d(x, 64, [3, 3], [1, 1], padding='SAME', activation_... 阅读全文
posted @ 2018-05-28 15:40 bonelee 阅读(3993) 评论(13) 推荐(1)
摘要: www.arocmag.com/getarticle/?aid=4e02d91c19b0cced Internet 蠕虫防范技术研究http://www.arocmag.com/article/1001-3695(2010)03-1032-03.html 基于统计分析建立流量动态临界线的蠕虫检测机制 阅读全文
posted @ 2018-05-28 14:42 bonelee 阅读(427) 评论(0) 推荐(0)
摘要: Write a program to check whether a given number is an ugly number. Ugly numbers are positive numbers whose prime factors only include 2, 3, 5. Example 阅读全文
posted @ 2018-05-27 23:07 bonelee 阅读(199) 评论(0) 推荐(0)
摘要: The set S originally contains numbers from 1 to n. But unfortunately, due to the data error, one of the numbers in the set got duplicated to another n 阅读全文
posted @ 2018-05-27 22:54 bonelee 阅读(185) 评论(0) 推荐(0)
摘要: Having said that, you can query sklearn.preprocessing.StandardScaler for the fit parameters: scale_ : ndarray, shape (n_features,) Per feature relativ 阅读全文
posted @ 2018-05-27 10:44 bonelee 阅读(377) 评论(0) 推荐(0)
摘要: 实验结果: MLP 隐藏层神经元个数 128 test confusion_matrix (SMOTE): 测试数据的混淆矩阵[[131946 120] [ 299 131767]] precision recall f1-score support 0 1.00 1.00 1.00 132066 阅读全文
posted @ 2018-05-26 12:02 bonelee 阅读(541) 评论(0) 推荐(0)
摘要: 多层感知机(MLP)原理简介 多层感知机(MLP,Multilayer Perceptron)也叫人工神经网络(ANN,Artificial Neural Network),除了输入输出层,它中间可以有多个隐层,最简单的MLP只含一个隐层,即三层的结构,如下图: 从上图可以看到,多层感知机层与层之间 阅读全文
posted @ 2018-05-26 10:28 bonelee 阅读(7396) 评论(0) 推荐(0)
摘要: 文章开始先讲下交叉验证,这个概念同样适用于这个划分函数 1.交叉验证(Cross-validation) 交叉验证是指在给定的建模样本中,拿出其中的大部分样本进行模型训练,生成模型,留小部分样本用刚建立的模型进行预测,并求这小部分样本的预测误差,记录它们的平方加和。这个过程一直进行,直到所有的样本都 阅读全文
posted @ 2018-05-26 10:01 bonelee 阅读(3674) 评论(0) 推荐(2)
上一页 1 ··· 149 150 151 152 153 154 155 156 157 ··· 274 下一页