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Original link: http://tecdat.cn/?p=24191In this article, I will focus on an example of the inference probability given a short data sequence. I will first introduce the theory of how to use Bayesian method for expectation reasoning, and then implement the theory in Python so that we can deal with these ideas. In order to make the article easier ...

Regression algorithm linear regression analysis Regression: continuous target value Linear regression: looking for a predictable trend Linear relationship: two-dimensional, linear relationship; Three dimensional, the target value is in a plane. linear model A function predicted by a linear combination of attributes: linear regression ...

The loss function used in this paper is the loss function constructed by KL discretization, without formula derivation; The code part is a user-defined function, not sklearn. The loss function constructed by discrete logistic regression KL is:     Where m is the number of samples; p_1 indicates the probability that the label is 1; y^{ ...

1. Linear Discrimination Criterion (LDA) 1.1 What is LDA? Unlike PCA variance maximization theory, linear discriminant analysis (LDA) is a generalization of Fisher's linear discriminant method, which uses Statistics，pattern recognition And machine learning methods, trying to find a linear combination of the characteristics of two types o ...

1. Concept understanding 1.1 mathematical basis Very boring, do not want to see can not see. 1.1.1 Bayesian probability 1.1.1.1 conditional probability Naive Bayesian classification algorithm is a classification method based on Bayesian theorem and the assumption of independence of feature conditions. Therefore, if you want to understa ...

Hierarchical clustering algorithm As the name suggests, hierarchical clustering is clustering layer by layer. Large clusters can be divided from top to bottom, which is called splitting method; It can also aggregate small categories from bottom to top, which is called condensation method; However, the bottom-up condensation method is commonly ...

When I installed tensorflow, I checked many articles, but none of them were particularly specific. This article is to draw on the strengths of others and summarize it according to its own installation process. Follow this article to install tensorflow 2.0 perfectly* Tensorflow is divided into__ Cpu__ And__ Gpu__ Version 2.0 or above, which gre ...

  1, Introduction 1.1 concept As shown in the figure, it is a decision tree. The square represents the decision block and the ellipse represents the terminating block, indicating that the conclusion has been reached and the operation can be terminated. The left and right arrow branch es are led out from the judgment module, which c ...

Task 1 & Task 2 data reading and data analysis The game data is text data, and each news is of variable length, which is stored in csv format. Therefore, you can directly use Pandas to complete the data reading operation. import pandas as pd train_df = pd.read_csv(r'train_set.csv', sep='\t') pd.read_csv common parameters: The read file ...

[1] The function Gaussian mixture in machine learning solves the components of each model [1.1] Gaussian texture parameter interpretation Available references: [sklearn] detailed explanation of various parameters and code implementation of mixture. Gaussian mixture_ Yakuho blog - CSDN blog_ gaussianmixture           [1.2] solution ...