涉及的一些知识: 机器人的自我定位 Sequential Importance Sampling Ref: http://scipy-cookbook.readthedocs.io/items/ParticleFilter.html Ref: http://blog.csdn.net/artista/article/details/51570878 Ref: https://www.youtube.com/watch?v=N7rH_VVtqRA Importance Sampling Revie…
看上去不错的网站:http://iacs-courses.seas.harvard.edu/courses/am207/blog/lecture-18.html SciPy Cookbook:http://scipy-cookbook.readthedocs.io/items/KalmanFiltering.html 良心视频:卡尔曼滤波器的原理以及在matlab中的实现 讲解思路貌似是在已知迭代结果的基础上做讲解,不是很透彻. 1. 用矩阵表示 2. 本质就是:二维高斯的协方差与samplin…
李航,第十一章,条件随机场 参考:[PGM] Markov Networks 携代码:用 Python 通过马尔可夫随机场(MRF)与 Ising Model 进行二值图降噪[推荐!] CRF:http://www.jianshu.com/p/55755fc649b1 概率无向图模型[基本性质] 团与最大团[基本性质] 链接:https://www.zhihu.com/question/35866596/answer/74187736 模型------ 首先什么是随机场呢,一组随机变量,他们样本…
Warning The sklearn.hmm module has now been deprecated due to it no longer matching the scope and the API of the project. It is scheduled for removal in the 0.17 release of the project. From: http://scikit-learn.sourceforge.net/stable/modules/hmm.htm…
1. 从贝叶斯方法(思想)说起 - 我对世界的看法随世界变化而随时变化 用一句话概括贝叶斯方法创始人Thomas Bayes的观点就是:任何时候,我对世界总有一个主观的先验判断,但是这个判断会随着世界的真实变化而随机修正,我对世界永远保持开放的态度. 1763年,民间科学家Thomas Bayes发表了一篇名为<An essay towards solving a problem in the doctrine of chances>的论文, 这篇论文发表后,在当时并未产生多少影响,但是在20…
Abstract Bayesian networks are a powerful probabilistic representation, and their use for classification has received considerable attention. However, they tend to perform poorly when learned in the standard way. This is attributable to a mismatch be…
scikit learn 模块 调参 pipeline+girdsearch 数据举例:文档分类数据集 fetch_20newsgroups #-*- coding: UTF-8 -*- import numpy as np from sklearn.pipeline import Pipeline from sklearn.linear_model import SGDClassifier from sklearn.grid_search import GridSearchCV from sk…
一.Scikit Learn中使用estimator三部曲 1. 构造estimator 2. 训练模型:fit 3. 利用模型进行预测:predict 二.模型评价 模型训练好后,度量模型拟合效果的常见准则有: 1.      均方误差(mean squared error,MSE): 2.      平均绝对误差(mean absolute error,MAE) 3.      R2 score:scikit learn线性回归模型的缺省评价准则,既考虑了预测值与真值之间的差异,也考虑了问题…
目录 5.3 使用LogisticRegressionCV进行正则化的 Logistic Regression 参数调优 一.Scikit Learn中有关logistics回归函数的介绍 1. 交叉验证 交叉验证用于评估模型性能和进行参数调优(模型选择).分类任务中交叉验证缺省是采用StratifiedKFold. sklearn.cross_validation.cross_val_score(estimator, X, y=None, scoring=None, cv=None, n_jo…
目录 Envoy 源码分析--network L4 filter manager FilterManagerImpl addWriteFilter addReadFilter addFilter initializeReadFilters onRead onWrite Envoy 源码分析--network L4 filter manager 申明:本文的 Envoy 源码分析基于 Envoy1.10.0. 承接Envoy 源码分析--network,上次 network 只分析到 L4 过滤,…