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String Kernels

This package contains an implementation of the Polynomial String Kernel and a linear time String Kernel algorithm as described in our paper, High Resolution Ancestry Deconvolution for Next Generation Genomic Data.

It offers

  • Linear time computation of two effective string kernels.

  • Compatibility with Scikit-Learn's Support Vector Machines (easy plug-in).

  • Multithreading.

Usage

To install the package, execute from the command line

pip install string-kernels

And then you're all set!

Assuming you have Scikit-Learn already installed, you can use Lodhi's string kernel via

fromsklearnimportsvmfromstringkernels.kernelsimportstring_kernelmodel=svm.SVC(kernel=string_kernel())

and the polynomial string kernel,

fromsklearnimportsvmfromstringkernels.kernelsimportpolynomial_string_kernelmodel=svm.SVC(kernel=polynomial_string_kernel())

For morer information read the docs or take a look at the notebook example.ipynb for further demonstration of usage.

If you end up using this in your research we kindly ask you to cite us! :)

About

Implementation of the Polynomial String Kernel and linear time String Kernel implementation. Compatible and ready for easy plug-in to Scikit-Learn's Support Vector Machines and supports multithreading.

Topics

algorithmsgenomicskernelsvmmachine-learningmultithreadingsequence-analysis

Resources

Readme
License
Activity

Stars

5 stars

Watchers

1 watching

Forks

1 fork
Report repository

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GitHub - weekend37/string-kernels: Implementation of the Polynomial String Kernel and linear time String Kernel implementation. Compatible and ready for easy plug-in to Scikit-Learn's Support Vector Machines and supports multithreading. · GitHub
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String Kernels
This package contains an implementation of the Polynomial String Kernel and a linear time String Kernel algorithm as described in our paper, High Resolution Ancestry Deconvolution for Next Generation Genomic Data. 

It offers
  • Linear time computation of two effective string kernels.
  • Compatibility with Scikit-Learn's Support Vector Machines (easy plug-in).
  • Multithreading.
Usage
To install the package, execute from the command line
pip install string-kernels

And then you're all set!
Assuming you have Scikit-Learn already installed, you can use Lodhi's string kernel via
fromsklearnimportsvmfromstringkernels.kernelsimportstring_kernelmodel=svm.SVC(kernel=string_kernel())
and the polynomial string kernel,
fromsklearnimportsvmfromstringkernels.kernelsimportpolynomial_string_kernelmodel=svm.SVC(kernel=polynomial_string_kernel())
For morer information read the docs or take a look at the notebook example.ipynb for further demonstration of usage.
If you end up using this in your research we kindly ask you to cite us! :)
About
Implementation of the Polynomial String Kernel and linear time String Kernel implementation. Compatible and ready for easy plug-in to Scikit-Learn's Support Vector Machines and supports multithreading.
Topics
algorithmsgenomicskernelsvmmachine-learningmultithreadingsequence-analysis
Resources
Readme
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Pythonscikit-learnPyPI Downloads
String Kernels
This package contains an implementation of the Polynomial String Kernel and a linear time String Kernel algorithm as described in our paper, High Resolution Ancestry Deconvolution for Next Generation Genomic Data. 

It offers
  • Linear time computation of two effective string kernels.
  • Compatibility with Scikit-Learn's Support Vector Machines (easy plug-in).
  • Multithreading.
Usage
To install the package, execute from the command line
pip install string-kernels

And then you're all set!
Assuming you have Scikit-Learn already installed, you can use Lodhi's string kernel via
fromsklearnimportsvmfromstringkernels.kernelsimportstring_kernelmodel=svm.SVC(kernel=string_kernel())
and the polynomial string kernel,
fromsklearnimportsvmfromstringkernels.kernelsimportpolynomial_string_kernelmodel=svm.SVC(kernel=polynomial_string_kernel())
For morer information read the docs or take a look at the notebook example.ipynb for further demonstration of usage.
If you end up using this in your research we kindly ask you to cite us! :)
About
Implementation of the Polynomial String Kernel and linear time String Kernel implementation. Compatible and ready for easy plug-in to Scikit-Learn's Support Vector Machines and supports multithreading.
Topics
algorithmsgenomicskernelsvmmachine-learningmultithreadingsequence-analysis
Resources
Readme
License
Activity
Stars
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Watchers
1 watching
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1 fork
Report repository
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GitHub - weekend37/string-kernels: Implementation of the Polynomial String Kernel and linear time String Kernel implementation. Compatible and ready for easy plug-in to Scikit-Learn's Support Vector Machines and supports multithreading. · GitHub
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Pythonscikit-learnPyPI Downloads
String Kernels
This package contains an implementation of the Polynomial String Kernel and a linear time String Kernel algorithm as described in our paper, High Resolution Ancestry Deconvolution for Next Generation Genomic Data. 

It offers
  • Linear time computation of two effective string kernels.
  • Compatibility with Scikit-Learn's Support Vector Machines (easy plug-in).
  • Multithreading.
Usage
To install the package, execute from the command line
pip install string-kernels

And then you're all set!
Assuming you have Scikit-Learn already installed, you can use Lodhi's string kernel via
fromsklearnimportsvmfromstringkernels.kernelsimportstring_kernelmodel=svm.SVC(kernel=string_kernel())
and the polynomial string kernel,
fromsklearnimportsvmfromstringkernels.kernelsimportpolynomial_string_kernelmodel=svm.SVC(kernel=polynomial_string_kernel())
For morer information read the docs or take a look at the notebook example.ipynb for further demonstration of usage.
If you end up using this in your research we kindly ask you to cite us! :)
About
Implementation of the Polynomial String Kernel and linear time String Kernel implementation. Compatible and ready for easy plug-in to Scikit-Learn's Support Vector Machines and supports multithreading.
Topics
algorithmsgenomicskernelsvmmachine-learningmultithreadingsequence-analysis
Resources
Readme
License
Activity
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GitHub - weekend37/string-kernels: Implementation of the Polynomial String Kernel and linear time String Kernel implementation. Compatible and ready for easy plug-in to Scikit-Learn's Support Vector Machines and supports multithreading. · GitHub
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Pythonscikit-learnPyPI Downloads
String Kernels
This package contains an implementation of the Polynomial String Kernel and a linear time String Kernel algorithm as described in our paper, High Resolution Ancestry Deconvolution for Next Generation Genomic Data. 

It offers
  • Linear time computation of two effective string kernels.
  • Compatibility with Scikit-Learn's Support Vector Machines (easy plug-in).
  • Multithreading.
Usage
To install the package, execute from the command line
pip install string-kernels

And then you're all set!
Assuming you have Scikit-Learn already installed, you can use Lodhi's string kernel via
fromsklearnimportsvmfromstringkernels.kernelsimportstring_kernelmodel=svm.SVC(kernel=string_kernel())
and the polynomial string kernel,
fromsklearnimportsvmfromstringkernels.kernelsimportpolynomial_string_kernelmodel=svm.SVC(kernel=polynomial_string_kernel())
For morer information read the docs or take a look at the notebook example.ipynb for further demonstration of usage.
If you end up using this in your research we kindly ask you to cite us! :)
About
Implementation of the Polynomial String Kernel and linear time String Kernel implementation. Compatible and ready for easy plug-in to Scikit-Learn's Support Vector Machines and supports multithreading.
Topics
algorithmsgenomicskernelsvmmachine-learningmultithreadingsequence-analysis
Resources
Readme
License
Activity
Stars
5 stars
Watchers
1 watching
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1 fork
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var __m = "*";
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GitHub - weekend37/string-kernels: Implementation of the Polynomial String Kernel and linear time String Kernel implementation. Compatible and ready for easy plug-in to Scikit-Learn's Support Vector Machines and supports multithreading. · GitHub
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Pythonscikit-learnPyPI Downloads
String Kernels
This package contains an implementation of the Polynomial String Kernel and a linear time String Kernel algorithm as described in our paper, High Resolution Ancestry Deconvolution for Next Generation Genomic Data. 

It offers
  • Linear time computation of two effective string kernels.
  • Compatibility with Scikit-Learn's Support Vector Machines (easy plug-in).
  • Multithreading.
Usage
To install the package, execute from the command line
pip install string-kernels

And then you're all set!
Assuming you have Scikit-Learn already installed, you can use Lodhi's string kernel via
fromsklearnimportsvmfromstringkernels.kernelsimportstring_kernelmodel=svm.SVC(kernel=string_kernel())
and the polynomial string kernel,
fromsklearnimportsvmfromstringkernels.kernelsimportpolynomial_string_kernelmodel=svm.SVC(kernel=polynomial_string_kernel())
For morer information read the docs or take a look at the notebook example.ipynb for further demonstration of usage.
If you end up using this in your research we kindly ask you to cite us! :)
About
Implementation of the Polynomial String Kernel and linear time String Kernel implementation. Compatible and ready for easy plug-in to Scikit-Learn's Support Vector Machines and supports multithreading.
Topics
algorithmsgenomicskernelsvmmachine-learningmultithreadingsequence-analysis
Resources
Readme
License
Activity
Stars
5 stars
Watchers
1 watching
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1 fork
Report repository
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GitHub - weekend37/string-kernels: Implementation of the Polynomial String Kernel and linear time String Kernel implementation. Compatible and ready for easy plug-in to Scikit-Learn's Support Vector Machines and supports multithreading. · GitHub
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Pythonscikit-learnPyPI Downloads
String Kernels
This package contains an implementation of the Polynomial String Kernel and a linear time String Kernel algorithm as described in our paper, High Resolution Ancestry Deconvolution for Next Generation Genomic Data. 

It offers
  • Linear time computation of two effective string kernels.
  • Compatibility with Scikit-Learn's Support Vector Machines (easy plug-in).
  • Multithreading.
Usage
To install the package, execute from the command line
pip install string-kernels

And then you're all set!
Assuming you have Scikit-Learn already installed, you can use Lodhi's string kernel via
fromsklearnimportsvmfromstringkernels.kernelsimportstring_kernelmodel=svm.SVC(kernel=string_kernel())
and the polynomial string kernel,
fromsklearnimportsvmfromstringkernels.kernelsimportpolynomial_string_kernelmodel=svm.SVC(kernel=polynomial_string_kernel())
For morer information read the docs or take a look at the notebook example.ipynb for further demonstration of usage.
If you end up using this in your research we kindly ask you to cite us! :)
About
Implementation of the Polynomial String Kernel and linear time String Kernel implementation. Compatible and ready for easy plug-in to Scikit-Learn's Support Vector Machines and supports multithreading.
Topics
algorithmsgenomicskernelsvmmachine-learningmultithreadingsequence-analysis
Resources
Readme
License
Activity
Stars
5 stars
Watchers
1 watching
Forks
1 fork
Report repository
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GitHub - weekend37/string-kernels: Implementation of the Polynomial String Kernel and linear time String Kernel implementation. Compatible and ready for easy plug-in to Scikit-Learn's Support Vector Machines and supports multithreading. · GitHub
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Pythonscikit-learnPyPI Downloads
String Kernels
This package contains an implementation of the Polynomial String Kernel and a linear time String Kernel algorithm as described in our paper, High Resolution Ancestry Deconvolution for Next Generation Genomic Data. 

It offers
  • Linear time computation of two effective string kernels.
  • Compatibility with Scikit-Learn's Support Vector Machines (easy plug-in).
  • Multithreading.
Usage
To install the package, execute from the command line
pip install string-kernels

And then you're all set!
Assuming you have Scikit-Learn already installed, you can use Lodhi's string kernel via
fromsklearnimportsvmfromstringkernels.kernelsimportstring_kernelmodel=svm.SVC(kernel=string_kernel())
and the polynomial string kernel,
fromsklearnimportsvmfromstringkernels.kernelsimportpolynomial_string_kernelmodel=svm.SVC(kernel=polynomial_string_kernel())
For morer information read the docs or take a look at the notebook example.ipynb for further demonstration of usage.
If you end up using this in your research we kindly ask you to cite us! :)
About
Implementation of the Polynomial String Kernel and linear time String Kernel implementation. Compatible and ready for easy plug-in to Scikit-Learn's Support Vector Machines and supports multithreading.
Topics
algorithmsgenomicskernelsvmmachine-learningmultithreadingsequence-analysis
Resources
Readme
License
Activity
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