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
> confint(lm.model, level=0.95) # After the ...
Posted by beerman on Tue, 08 Mar 2022 14:48:27 +0100
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 ...
Posted by BrentNorin on Tue, 08 Mar 2022 08:35:23 +0100
(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 ...
Posted by GeertDD on Sun, 06 Mar 2022 17:43:45 +0100
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 ...
Posted by mattkirkey on Sun, 06 Mar 2022 16:59:02 +0100
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.
Posted by deadimp on Mon, 28 Feb 2022 05:40:23 +0100
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 ...
Posted by vivek on Sun, 20 Feb 2022 08:42:28 +0100
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 ...
Posted by rsassine on Fri, 18 Feb 2022 02:03:30 +0100
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 ...
Posted by prometheuzz on Thu, 17 Feb 2022 18:47:12 +0100
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 ...
Posted by Elle0000 on Thu, 17 Feb 2022 02:42:48 +0100
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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 ...
Posted by aviavi on Sat, 12 Feb 2022 05:43:10 +0100