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Fitting, as the name suggests, is to find the mathematical relationship between data through the analysis of data. The deeper the understanding of the essence of this relationship, the higher the degree of fitting, and the clearer the relationship between data. Fitting includes linear fitting and nonlinear fitting (polynomial fitting). This pap ...

There are many ways to measure the performance of the model. The index to evaluate the performance of the classifier is generally the classification accuracy, which is defined as the ratio of the number of samples correctly classified by the classifier to the total number of samples for a given test data set. The commonly used evaluation indexe ...

Why dimensionality reduction? reason High dimensional machine learning has a large number of features (variables), which have certain obstacles to machine learning calculation, but some of them may have certain correlation. Under the condition of ensuring that there is no loss of too much information, the features are processed into a group o ...

Linear algebra and code implementation (I) vector background The Linear Algebra I studied in university is a little forgotten now, and I am not proficient in the code implementation; This column mainly reviews the basis of linear algebra and implements the code part; 1. Some basic concepts Essence: the basic expression of a group of numbers ...

1. Likelihood function of GMM about K = 3   ,   μ = [ ...

What is feature engineering? Feature engineering is a process that uses professional background knowledge and skills to process data, so that features can play a better role in machine learning algorithms. Significance: it will directly affect the effect of machine learning Contents of Feature Engineering: feature extraction Feature preproce ...

1, HOG feature extraction principle    HOG feature extraction process can be divided into five parts: detection window, normalized image, calculating gradient, statistical histogram, normalization of gradient histogram, and obtaining HOG feature vector. Detection window:    HOG divides the image through window and blo ...

Time series data analysis Reference Zhihu article: time series data analysis 101, author: Li Jianyang In addition, it also adds the evaluation method summary of classification and clustering + python implementation. 1 prepare and process time series data 1.1 preparing data sets Looking for ready-made data in open source data ware ...

PyTorch learning -- handwritten numeral recognition    MNIST dataset, which contains 70000 28 × 28 handwritten numeral data set, which is divided into 60000 training samples and 10000 test samples. Ⅰ. data reader import torch from torch import nn from torch import optim from torch.nn.parameter import Parameter import ...

Chapter III classification preface In the last chapter, we learned how to complete a machine learning task, in which many models are used. In this chapter, we will have a deeper understanding of the classification model, including binary classification, multi class classification, multi label classification and multi output classificati ...