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1, Construction of decision tree decision tree is a kind of common machine learning algorithm. It makes decisions based on tree structure. Step by step from the root node to the leaf node (decision). All data will eventually fall to leaf nodes, which can be classified or regressed. Decision tree Advantages: the calculation complexity ...

1 Preface Hi, everyone, this is senior Dan Cheng. Today, I'm doing an e-commerce sales forecast analysis. This is just a demo. I'm trying to analyze the film data and visualize the system Bi design help, problem opening guidance, technical solutions 🇶746876041 2 principle of spam SMS / Email Classification Algorithm Spam content is oft ...

6.2.1 data set introduction The data used in this OCR experiment is based on Task 4.3:Word Recognition in icdar2015 incident scene text. This is a word recognition task. Remove some pictures to simplify the difficulty of this experiment. The data set contains many text areas in natural scene images. The training set in the original data co ...

Scikit learn is a very beautiful one machine learning Libraries. Sometimes, using these libraries can save you a lot of time. At least, we can use them Python , it should be difficult to write such fast code Scikit learn has some official documents, but personally, I don't think many things in its documents are clear. When it says the principl ...

Reference book "deep learning practice" by Yang Yun and Du Fei softmax implementation exercise In the exercises in this chapter, we will gradually complete: 1. Be familiar with using CIFAR-10 dataset2. Code softmax_ loss_ The naive function uses an explicit loop to calculate the loss function and the gradient3. Code softmax_ loss_ ...

House price forecast Original question: https://www.kaggle.com/c/house-prices-advanced-regression-techniques/data?select=train.csv reference resources: https://blog.csdn.net/qq_29153321/article/details/103967670 The house price prediction experiment analyzes 1460 house price data and the attributes of 80 houses, establishes a regression mode ...

1. Origin: GAN Structure and principle Before introducing DeblurGANv2, we need to know about GAN. GAN's initial application is image generation, that is, generating images according to the training set, such as handwritten digital images, face images, animal images, etc. its main structure is as follows: Let's start from the bottom left of ...

Cartographer installation tutorial and pit record Copyright notice: This article is reproduced from the original article of CSDN blogger "white boots", in accordance with CC 4.0 BY-SA copyright agreement. Please attach the original source link and this notice. Original link: https://blog.csdn.net/weixin_44684139/article/details/104 ...

Graphical K-Means algorithm This paper introduces a common unsupervised learning algorithm, called K-Means algorithm: K-Means algorithm. K-Means algorithm is the most basic and important algorithm in unsupervised learning, especially clustering algorithm. It is very simple to implement. Clustering effect is also very good, so it is widely use ...

1, Dataset Download Link: https://pan.baidu.com/s/1_7blbYJc0ouCGmqe8kBnTw extraction code: c6ex copy this content and open Baidu online disk mobile App, which is more convenient to operate 2, Training model 1. Define data initialization import torchvision.transforms as transforms image_size=(224,224) # data_transforms=transforms.Compose([ ...