Logistic regression is an example of supervised learning. It is used to calculate or predict the probability of a binary (yes/no) event occurring. An example of logistic regression could be applying machine learning to determine if a person is likely to be infected with COVID-19 or not. Sin...
logistic regression in a non-mathematical manner for people who are not Machine Learning practitioners, so if you want to go deeper, or are looking for a more profound of mathematical explanation, take a look at the following video, it explains very well everything we have mentioned in this ...
神经网络基础篇:详解logistic 损失函数(Explanation of logistic regression cost function) 详解logistic 损失函数 在本篇博客中,将给出一个简洁的证明来说明逻辑回归的损失函数为什么是这种形式。 回想一下,在逻辑回归中,需要预测的结果^yy^,可以表示为^y=σ(wTx+b)y^=σ(wTx+b),σσ是熟悉的SS型函数 σ(z...
This blue curve that you see is not a decision boundary. Its simply in a way is transformed response from binary response which we model using logistic regression. Decision boundary of logistic regression is always a line [ or a plane , or a hyper-plane for higher dimension]. Best way to...
NCSS Statistical Software Logistic Regression NCSS.com Now, using a simple example from horse racing, if one horse has 8:1 odds of winning and a second horse has 4:1 odds of winning, how do you compare these two horses? One obvious way is to look at the ratio of their odds. The ...
However, if one approaches logistic regression from a combined Bayesian and Maximum Entropy viewpoint, the explanation of its origin is relatively simple and direct. The perspective given here proceeds in two major steps. First, formally manipulate the probability symbols to rearrange them into the ...
Deep Learning with Theano - Part 1: Logistic RegressionOver the last ten years the subject of deep learning has been one of the most discussed fields in machine learning and artificial intelligence. It has produced state-of-the-art results in areas as diverse as computer vision, image ...
Thank you for this detailed explanation/tutorial on Logistic Regression. I have few queries related to Logistic Regression which I am not able to find answers over the internet or in books. It would be of great help if you could help me understand these uncleared questions. ...
Motivation One of the most common comments I hear is that logistic regression (also called Binomial regression) is some kind of “advanced magic”, “machine learning”, “artificial intelligence” or “big data”. This is not true. In this post, I will
Explanation Why is the logistic classification model specified in this manner? Why is the logistic function used to transform the linear combination of inputs ? The simple answer is that we would like to do something similar to what we do in alinear regression model: use a linear combination ...