GeneExpression | 基因表达式编程,java代码实现。主要实现二分类器,和多分类器。 | Machine Learning library
kandi X-RAY | GeneExpression Summary
kandi X-RAY | GeneExpression Summary
基因表达式编程 (Gene Expression Programming,GEP)是C.Ferreira在遗传算法和遗传程序设计的基础上提出的一种新的遗传算法,它结合了遗传算法和遗传程序设计的优点,建立了一种新的基因编码方式和结果变形形式。.
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Top functions reviewed by kandi - BETA
- Test program
- Read data from a file
- Performs test
- Set values
- Main entry point
- Get feature information
- Get pareto font
- Generate superset
- Single feature count
- Initializes the population
- Select the population
- Recomate two points
- Main method
- Gets the order
- Get super set
- Gets the fitness function
- Returns the valid length of an indiv
- Get sub feature set
- Set individual
- Return the average fitness for the population
- Get the fitness function
- Get fitness
- Gets fitness
- Demonstrates the main test program
GeneExpression Key Features
GeneExpression Examples and Code Snippets
Community Discussions
Trending Discussions on GeneExpression
QUESTION
Hello I am trying to speed up a block of code that is currently working, but is quite slow with the amount of data that I have. I need to identify the top n% highest value in a row and subsequently use this to make an average by subsetting a dataframe and averaging the values of the subset. Any help or suggestions would be appreciated. This is my current approach:
...ANSWER
Answered 2020-Jul-16 at 09:56Here's a smaller version of your example along with my base R solution. Chances are there's also a neat tidyverse way of doing this but I wouldn't know.
QUESTION
I'm trying to understand the answer to this question using R and I'm struggling a lot.
The dataset for the R code can be found with this code
...ANSWER
Answered 2018-Aug-11 at 01:03You question seems to be about understanding the function apply()
.
For the technical description, see ?apply
.
My quick explanation: the apply()
line of code in your question applies the following function to each of the rows of geneExpression
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install GeneExpression
You can use GeneExpression like any standard Java library. Please include the the jar files in your classpath. You can also use any IDE and you can run and debug the GeneExpression component as you would do with any other Java program. Best practice is to use a build tool that supports dependency management such as Maven or Gradle. For Maven installation, please refer maven.apache.org. For Gradle installation, please refer gradle.org .
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