Programmer Think

I Linear regression 1. lm() function returns the prediction model of input variables, and the returned results can be used with many functions. > lm.model <- lm(wt ~ mpg, data = mtcars) > coefficients(lm.model) # Extraction coefficient (Intercept) mpg 6.047255 -0.140862 > confint(lm.model, level=0.95) # After the ...

Background introduction Since 2015, the shared automobile industry has "let a hundred flowers bloom" and many projects have received huge financing. However, due to the heavy model, high operating costs, inability to make profits and other problems, one after another shared car companies closed down due to the rupture of the capital ...

(3) Probability and information theory) 2, Linear algebra Purpose: it is mainly to reduce the dimension of data and restore or build the target with the least data 2.1 eigenvalue decomposition Only symmetric positive definite matrix can be decomposed into eigenvalues. Eigenvalue decomposition: A = P * B * PT, where B is the diagonal mat ...

After sequencing, we can observe the presence of different subtypes of mutations based on the data of different genotypes. There is only one file to be prepared. The format is as follows:   This is the risk model I analyzed in TCGA gastric cancer (STAD) database. The gastric cancer data is divided into high and low risks, and the data ca ...

preface After differential expression, most of us will see whether our differential gene screening can show the grouping results, and will choose the heat map, mainly the heat map skill clustering, which can also show the size of expression, which is very intuitive. Therefore, in this issue, we will talk about the drawing method of heat map. ...

When I see the logistic regression classifier, my first reaction is that it's not a statistical logistic regression. In fact, it's the same. I've written about the practice of logistic regression before. I'll write it again under the framework of machine learning today. logistic regression is a supervised learning method that predicts class ...

01. Preface In the near future, it is expected that the emerging digital gene expression (DGE) technology will surpass microarray technology in many applications of functional genomics. One of the basic data analysis tasks, especially gene expression research, involves determining whether there is evidence that transcripts or exons are signifi ...

Original link: http://tecdat.cn/?p=22422    In this paper, we describe a flexible competitive risk regression model. The regression model is designated as the transition probability, that is, the cumulative incidence in the competitive risk setting. The model includes the model of Fine and Gray (1999) as a special case. This can be used to te ...

1, Introduction of PWM and PFM Motif refers to the DNA sequence pattern that transcription factors prefer to bind or the sequence pattern that RNA binding proteins prefer to bind. PWM is generally used to represent motif. The process of making PWM is as follows: First, calculate the base frequency of each position of all sequences to obt ...

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 How to input the adjacency matrix stored on disk into R program is the starting point of social network analysis. The basic data structure and c ...