In the world of machine learning, accuracy is crucial. You strive to make your model more accurate by tuning and optimizing parameters, but you can never achieve 100% accuracy. This is the harsh reality of your prediction/classification models; they can never be zero-error. In this article, I will discuss why this happens and other methods … Read more
Click on the top “Visual Learning for Beginners“, select “Star” or “Pin“ Essential content delivered to you first All algorithms in machine learning rely on minimizing or maximizing a certain function, which we call the objective function. The set of functions to be minimized is referred to as the loss function. The loss function measures … Read more
Follow our public account to discover the beauty of CV technology Spatial-temporal prediction learning is a field with a wide range of application scenarios, such as weather forecasting, traffic flow prediction, precipitation prediction, autonomous driving, and human motion prediction. When it comes to spatial-temporal prediction, we must mention the classic model ConvLSTM and the most … Read more
Author: Little Cola Demon King @ Zhihu (Authorized) Source: https://zhuanlan.zhihu.com/p/378822530 Editor: Jishi Platform This article summarizes how to choose the appropriate loss function for different application scenarios, compares the advantages and disadvantages of different loss functions, and provides relevant PyTorch code. Direct Results: Image excerpted from the end of this article Main Text: In both … Read more
This article will coverthe essence of the Loss Function principles of the Loss Functionand the algorithms to help you understand the Loss Function Loss Function . Loss Function 1.Loss Function essence Machine Learning’s “Three Steps”:Select a family of models,define the loss function to quantify prediction errors,and find the optimal model parameters that minimize the loss … Read more