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Conditional generation countermeasure network CGAN CGAN is one of the earliest GAN innovations that make the generation of target data possible. It can be said to be the most influential one. Next, it introduces the working mode of CGAN and how to implement its small-scale version with MNIST dataset. CGAN principle The generator learns to ge ...

Stacking integration algorithm can be understood as a two-layer integration. The first layer contains multiple basic classifiers to provide the prediction results (meta features) to the second layer, while the classifier of the second layer is usually logistic regression. He takes the results of the first layer classifier as features to fit ...

Summary of relevant codes of machine learning Summary of machine learning related codes XGBoost There is one in sklearn, but there is another one with more powerful functions, as long as pip3 install xgboost Can be installed, but this installation process is really twists and turns. Then, we need to know the general process used by xgboo ...

The difference and relation between linear regression and logistic regression Both linear regression and logistic regression are linear regression in a broad sense. But they are different. methodIndependent variable (characteristic)Dependent variable (result)relationshipapplicationLinear regressionContinuous or discreteContinuous real num ...

Quickly review the soft voting and hard voting in the integration methodThe integration method is to combine the results of two or more separate machine learning algorithms and try to produce more accurate results than any single algorithm.In soft voting, the probability of each category is averaged to produce results. For example, if algorithm ...

Python wechat ordering applet course video https://edu.csdn.net/course/detail/36074 Python actual combat quantitative transaction financial management system https://edu.csdn.net/course/detail/35475 We are Random sampling and probability distribution in Python (II) This paper introduces how to sample a probability distribution with Python's ...

What is numpy A basic library for scientific calculation in Python, which focuses on numerical calculation. It is also the basic library of most Python scientific calculation libraries. It is mostly used to perform numerical operations on large and multi-dimensional arrays Axis In numpy, it can be understood as direction, which is expres ...

Abstract: This paper mainly explains the process of realizing Chinese text classification by CNN, and compares it with Bayesian, decision tree, logistic regression, random forest, KNN, SVM and other classification algorithms. This article is shared from Huawei cloud community< [Python artificial intelligence] 21 Detailed explanation of Wo ...

Introduction to Dropout 1.1 Reasons for Dropout _In the machine learning model, if there are too many parameters of the model and too few training samples, the trained model can easily be fitted. When training the neural network, we often encounter the problem of fitting, which is manifested in the following aspects: the loss function of ...

「 🍔 Customize training template 🍔」 Example of eliminating online game based on document shadow I believe you have the same confusion as me when writing projects with paste: The encapsulation of advanced APIs is too good, and it is difficult to add some functions when they need to be customized; The low-level API function is very single. ...