Naïve Bayes Classifier. We will use, specifically, the Bernoulli-Dirichlet model for text classification, We will train the model using both the Maximum Likelihood estimates and Bayesian updating, and compare these in terms of predictive success, and…

Github上的一个开源项目,文档讲得极清晰 Github - https://github.com/dennybritz/cnn-text-classification-tf 原文- http://www.wildml.com/2015/12/implementing-a-cnn-for-text-classification-in-tensorflow/ In this post we will implement a model similar to Kim Yoon’s Convolut…

Ref: Combining CNN and RNN for spoken language identification Ref: Convolutional Methods for Text [1] CONVOLUTIONAL, LONG SHORT-TERM MEMORY, FULLY CONNECTED DEEP NEURAL NETWORKS [2] Efficient Character-level Document Classification by Combining Convo…

参考:Fitting a Model by Maximum Likelihood 最大似然估计是用于估计模型参数的,首先我们必须选定一个模型,然后比对有给定的数据集,然后构建一个联合概率函数,因为给定了数据集,所以该函数就是以模型参数为自变量的函数,通过求导我们就能得到使得该函数值(似然值)最大的模型参数了. Maximum-Likelihood Estimation (MLE) is a statistical technique for estimating model parameters…

Reference:MLE vs MAP. Maximum Likelihood Estimation (MLE) and Maximum A Posteriori (MAP), are both a method for estimating some variable in the setting of probability distributions or graphical models. They are similar, as they compute a single estim…

先不要想其他的,首先要在大脑里形成概念! 最大似然估计是什么意思?呵呵,完全不懂字面意思,似然是个啥啊?其实似然是likelihood的文言翻译,就是可能性的意思,所以Maximum Likelihood可以直接叫做最大可能性估计,这就好理解了,就是要求出最大的可能性(下的那个参数). 一些最基本的概念:总体X,样本x,分布P(x:θ),随机变量(连续.离散),模型参数,联合分布,条件分布 而似然函数在形式上,其实就是样本的联合密度:L(θ)= L(x1,x2,-,xn:θ)= ΠP(xi:θ)…

参考: 1.Understanding Convolutional Neural Networks for NLP 2.Implementing a CNN for Text Classification in TensorFlow…

1.What is Maximum Likelihood? 极大似然是一种找到最可能解释一组观测数据的函数的方法. Maximum Likelihood is a way to find the most likely function to explain a set of observed data. 在基本统计学中,通常给你一个模型来计算概率.例如,你可能被要求找出X大于2的概率,给定如下泊松分布:X ~ Poisson (2.4).在这个例子中,已经给定了你泊松分布的参数 λ(2.4),…

https://blog.csdn.net/BitCs_zt/article/details/82938086 列出自己阅读的text classification论文的列表,以后有时间再整理相应的笔记.阅读价值评分纯粹是基于自己对于文章的理解,标准包括:动机.方法.数据集质量.实验安排.相关工作等,满分为5.列表如下: 名称 所属会议 类型 时间 阅读价值Recurrent Convolutional Neural Networks for Text Classification AAAI l…

Imagination is an outcome of what you learned. If you can imagine the world, that means you have learned what the world is about. Actually we don't know how we see, at lease it's really hard to know, so we can't program to tell a machine to see. One…