CS-7641-Randomized-Optimization | The code is for Gatech CS7641 Assignment 2 Randomized
kandi X-RAY | CS-7641-Randomized-Optimization Summary
kandi X-RAY | CS-7641-Randomized-Optimization Summary
CS-7641-Randomized-Optimization is a Java library. CS-7641-Randomized-Optimization has no bugs, it has no vulnerabilities and it has low support. However CS-7641-Randomized-Optimization build file is not available. You can download it from GitHub.
The code is for Gatech CS7641 Assignment 2 Randomized Optimization. My implementation was base on ABAGAIL package and jython environment. So the newest ABAGAIL.jar and jython 2.7 needed to be installed. Also the location of the ABAGAIL.jar file needs to be specified in each script, in the sys.path.append command in first few lines of each scripts. After changing that, all my script can be ran like [jython ANN_back.py] to get the output to STDOUT and local log files.
The code is for Gatech CS7641 Assignment 2 Randomized Optimization. My implementation was base on ABAGAIL package and jython environment. So the newest ABAGAIL.jar and jython 2.7 needed to be installed. Also the location of the ABAGAIL.jar file needs to be specified in each script, in the sys.path.append command in first few lines of each scripts. After changing that, all my script can be ran like [jython ANN_back.py] to get the output to STDOUT and local log files.
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CS-7641-Randomized-Optimization has a low active ecosystem.
It has 1 star(s) with 0 fork(s). There are no watchers for this library.
It had no major release in the last 6 months.
CS-7641-Randomized-Optimization has no issues reported. There are no pull requests.
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The latest version of CS-7641-Randomized-Optimization is current.
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CS-7641-Randomized-Optimization has no bugs reported.
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CS-7641-Randomized-Optimization has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
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CS-7641-Randomized-Optimization does not have a standard license declared.
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CS-7641-Randomized-Optimization releases are not available. You will need to build from source code and install.
CS-7641-Randomized-Optimization has no build file. You will be need to create the build yourself to build the component from source.
Top functions reviewed by kandi - BETA
kandi has reviewed CS-7641-Randomized-Optimization and discovered the below as its top functions. This is intended to give you an instant insight into CS-7641-Randomized-Optimization implemented functionality, and help decide if they suit your requirements.
- Estimate the k - means for the given dataset
- Estimate the mixture distribution
- Estimate the cluster centers
- Estimates the covariance matrix
- Computes the singular value decomposition
- Performs a QR decomposition on a sub - matrix
- Creates the transpose of this matrix
- Gets a sub - matrix from this matrix
- Train the network
- Performs the decomposition
- Trains the distribution
- Estimate the probability of the transition
- Train the genetic algorithm
- Trains the state on the policy
- Load a maze from a text file
- Train a new value
- Estimate the ensemble
- Makes a candidate
- Perform the decomposition decomposition
- Trains the current state
- Choose a splitter from a list of nodes
- Performs a decomposition using gaussian elimination
- Decomposes the matrix
- Calculates the best fitness for a given instance
- Runs all the iterations and prints the results
- Estimate the mixture probabilities
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CS-7641-Randomized-Optimization Key Features
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CS-7641-Randomized-Optimization Examples and Code Snippets
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Vulnerabilities
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Install CS-7641-Randomized-Optimization
You can download it from GitHub.
You can use CS-7641-Randomized-Optimization 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 CS-7641-Randomized-Optimization 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 .
You can use CS-7641-Randomized-Optimization 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 CS-7641-Randomized-Optimization 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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For any new features, suggestions and bugs create an issue on GitHub.
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