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BayesianKit - Cocoa Objective-C Framework for a naive bayesian classifier

BayesianKit is a Mac OS X Framework written by Samuel Mendes in Objective-C 2.0 and released under BSD 3-clauses license. BayesianKit offers a simple, ready to use, implementation for a bayesian classifier. A command line utility is also provided.

Dependencies

  • ParseKit used for the default tokenizer
  • appledoc used to generate the headers' documentation

Both of them are included as submodules. After having cloned the repository type:

git submodule init
git submodule update

However appledoc needs Doxygen which is not provided.

Xcode Project

The BayesianKit project consists of 3 targets:

  • BayesianKit : The BayesianKit framework.
  • Bayes : The command line utility.
  • Install Documentation : The script running appledoc.

BayesianKit usage

The default classifier comes with a tokenizer based on ParseKit. Quite efficient when training on source code. It also implements and use the Robinson-Fisher combiner on probabilities. Both the tokenizer and combiner can be changed, however note that they are not saved along the training. Hence if you load a classifier from a file, you must reset the tokenizer and/or combiner.

Creating and Training a new classifier

BKClassifier *classifier = [[BKClassifier alloc] init];
[classifier trainWithString:@"one two three four five"
forPoolNamed:@"english"];
[classifier trainWithString:@"un deux trois quatre cinq"
forPoolNamed:@"french"];

Saving and reloading the training data

[classifier writeToFile:@"counting.bks"]
// Another day, in a different process
BKClassifier *anotherOne;
anotherOne = [BKClassifier classifierWithContentsOfFile:@"counting.bks"];

Using the classifier to make a guess

NSDictionary *results = [anotherOne guessWithString:@"three platypuses"];
NSLog(@"%@", results);

The output is:

$ {
english = "0.9999";
}

Bayes

This tool was intended to test quickly the classifier, and works only with files. A manpage is also provided with every details.

Installation

From the root directory of the project:

sudo cp build/Release/bayes /usr/local/bin/
sudo cp docs/man/man1/bayes.1 /usr/local/share/man/man1/

Training with a save file

bayes -f save.bks -s -t english shakespeare.txt -t french moliere.txt

Guessing based on this training

bayes -f save.bks -g mystery.txt

LICENSE

Copyright (c) 2010, Samuel Mendes

All rights reserved.

Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:

  • Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.

  • Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.

  • Neither the name of ᐱ nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission.

THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

Samuel Mendes samuel.mendes@gmail.com

About

A Cocoa framework implementing a bayesian classifier

Resources

Readme
BSD-3-Clause license
Activity

Stars

69 stars

Watchers

6 watching

Forks

4 forks
Report repository

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Contributors

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GitHub - lok/BayesianKit: A Cocoa framework implementing a bayesian classifier · GitHub
Skip to content
BranchesTags
Repository files navigation
BayesianKit - Cocoa Objective-C Framework for a naive bayesian classifier
BayesianKit is a Mac OS X Framework written by Samuel Mendes in Objective-C 2.0
and released under BSD 3-clauses license. BayesianKit offers a simple, ready to
use, implementation for a bayesian classifier. A command line utility is also
provided.
Dependencies
  • ParseKit used for the default tokenizer
  • appledoc used to generate the
headers' documentation
Both of them are included as submodules. After having cloned the repository
type:
git submodule init
git submodule update

However appledoc needs Doxygen which is
not provided.
Xcode Project
The BayesianKit project consists of 3 targets:
  • BayesianKit : The BayesianKit framework.
  • Bayes : The command line utility.
  • Install Documentation : The script running appledoc.
BayesianKit usage
The default classifier comes with a tokenizer based on ParseKit. Quite efficient
when training on source code. It also implements and use the Robinson-Fisher
combiner on probabilities. Both the tokenizer and combiner can be changed,
however note that they are not saved along the training. Hence if you load a
classifier from a file, you must reset the tokenizer and/or combiner.
Creating and Training a new classifier
BKClassifier *classifier = [[BKClassifier alloc] init];
[classifier trainWithString:@"one two three four five"
forPoolNamed:@"english"];
[classifier trainWithString:@"un deux trois quatre cinq"
forPoolNamed:@"french"];

Saving and reloading the training data
[classifier writeToFile:@"counting.bks"]
// Another day, in a different process
BKClassifier *anotherOne;
anotherOne = [BKClassifier classifierWithContentsOfFile:@"counting.bks"];

Using the classifier to make a guess
NSDictionary *results = [anotherOne guessWithString:@"three platypuses"];
NSLog(@"%@", results);

The output is:
$ {
english = "0.9999";
}

Bayes
This tool was intended to test quickly the classifier, and works only with
files. A manpage is also provided with every details.
Installation
From the root directory of the project:
sudo cp build/Release/bayes /usr/local/bin/
sudo cp docs/man/man1/bayes.1 /usr/local/share/man/man1/

Training with a save file
bayes -f save.bks -s -t english shakespeare.txt -t french moliere.txt

Guessing based on this training
bayes -f save.bks -g mystery.txt

LICENSE
Copyright (c) 2010, Samuel Mendes
All rights reserved.
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:
  • Redistributions of source code must retain the above copyright
notice, this list of conditions and the following disclaimer.
  • Redistributions in binary form must reproduce the above copyright
notice, this list of conditions and the following disclaimer in the
documentation and/or other materials provided with the distribution.
  • Neither the name of ᐱ nor the names of its
contributors may be used to endorse or promote products derived
from this software without specific prior written permission.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
"AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED
TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
Samuel Mendes samuel.mendes@gmail.com
About
A Cocoa framework implementing a bayesian classifier
Resources
Readme
BSD-3-Clause license
Activity
Stars
69 stars
Watchers
6 watching
Forks
4 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
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GitHub - lok/BayesianKit: A Cocoa framework implementing a bayesian classifier · GitHub
Skip to content
BranchesTags
Repository files navigation
BayesianKit - Cocoa Objective-C Framework for a naive bayesian classifier
BayesianKit is a Mac OS X Framework written by Samuel Mendes in Objective-C 2.0
and released under BSD 3-clauses license. BayesianKit offers a simple, ready to
use, implementation for a bayesian classifier. A command line utility is also
provided.
Dependencies
  • ParseKit used for the default tokenizer
  • appledoc used to generate the
headers' documentation
Both of them are included as submodules. After having cloned the repository
type:
git submodule init
git submodule update

However appledoc needs Doxygen which is
not provided.
Xcode Project
The BayesianKit project consists of 3 targets:
  • BayesianKit : The BayesianKit framework.
  • Bayes : The command line utility.
  • Install Documentation : The script running appledoc.
BayesianKit usage
The default classifier comes with a tokenizer based on ParseKit. Quite efficient
when training on source code. It also implements and use the Robinson-Fisher
combiner on probabilities. Both the tokenizer and combiner can be changed,
however note that they are not saved along the training. Hence if you load a
classifier from a file, you must reset the tokenizer and/or combiner.
Creating and Training a new classifier
BKClassifier *classifier = [[BKClassifier alloc] init];
[classifier trainWithString:@"one two three four five"
forPoolNamed:@"english"];
[classifier trainWithString:@"un deux trois quatre cinq"
forPoolNamed:@"french"];

Saving and reloading the training data
[classifier writeToFile:@"counting.bks"]
// Another day, in a different process
BKClassifier *anotherOne;
anotherOne = [BKClassifier classifierWithContentsOfFile:@"counting.bks"];

Using the classifier to make a guess
NSDictionary *results = [anotherOne guessWithString:@"three platypuses"];
NSLog(@"%@", results);

The output is:
$ {
english = "0.9999";
}

Bayes
This tool was intended to test quickly the classifier, and works only with
files. A manpage is also provided with every details.
Installation
From the root directory of the project:
sudo cp build/Release/bayes /usr/local/bin/
sudo cp docs/man/man1/bayes.1 /usr/local/share/man/man1/

Training with a save file
bayes -f save.bks -s -t english shakespeare.txt -t french moliere.txt

Guessing based on this training
bayes -f save.bks -g mystery.txt

LICENSE
Copyright (c) 2010, Samuel Mendes
All rights reserved.
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:
  • Redistributions of source code must retain the above copyright
notice, this list of conditions and the following disclaimer.
  • Redistributions in binary form must reproduce the above copyright
notice, this list of conditions and the following disclaimer in the
documentation and/or other materials provided with the distribution.
  • Neither the name of ᐱ nor the names of its
contributors may be used to endorse or promote products derived
from this software without specific prior written permission.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
"AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED
TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
Samuel Mendes samuel.mendes@gmail.com
About
A Cocoa framework implementing a bayesian classifier
Resources
Readme
BSD-3-Clause license
Activity
Stars
69 stars
Watchers
6 watching
Forks
4 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
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GitHub - lok/BayesianKit: A Cocoa framework implementing a bayesian classifier · GitHub
Skip to content
BranchesTags
Repository files navigation
BayesianKit - Cocoa Objective-C Framework for a naive bayesian classifier
BayesianKit is a Mac OS X Framework written by Samuel Mendes in Objective-C 2.0
and released under BSD 3-clauses license. BayesianKit offers a simple, ready to
use, implementation for a bayesian classifier. A command line utility is also
provided.
Dependencies
  • ParseKit used for the default tokenizer
  • appledoc used to generate the
headers' documentation
Both of them are included as submodules. After having cloned the repository
type:
git submodule init
git submodule update

However appledoc needs Doxygen which is
not provided.
Xcode Project
The BayesianKit project consists of 3 targets:
  • BayesianKit : The BayesianKit framework.
  • Bayes : The command line utility.
  • Install Documentation : The script running appledoc.
BayesianKit usage
The default classifier comes with a tokenizer based on ParseKit. Quite efficient
when training on source code. It also implements and use the Robinson-Fisher
combiner on probabilities. Both the tokenizer and combiner can be changed,
however note that they are not saved along the training. Hence if you load a
classifier from a file, you must reset the tokenizer and/or combiner.
Creating and Training a new classifier
BKClassifier *classifier = [[BKClassifier alloc] init];
[classifier trainWithString:@"one two three four five"
forPoolNamed:@"english"];
[classifier trainWithString:@"un deux trois quatre cinq"
forPoolNamed:@"french"];

Saving and reloading the training data
[classifier writeToFile:@"counting.bks"]
// Another day, in a different process
BKClassifier *anotherOne;
anotherOne = [BKClassifier classifierWithContentsOfFile:@"counting.bks"];

Using the classifier to make a guess
NSDictionary *results = [anotherOne guessWithString:@"three platypuses"];
NSLog(@"%@", results);

The output is:
$ {
english = "0.9999";
}

Bayes
This tool was intended to test quickly the classifier, and works only with
files. A manpage is also provided with every details.
Installation
From the root directory of the project:
sudo cp build/Release/bayes /usr/local/bin/
sudo cp docs/man/man1/bayes.1 /usr/local/share/man/man1/

Training with a save file
bayes -f save.bks -s -t english shakespeare.txt -t french moliere.txt

Guessing based on this training
bayes -f save.bks -g mystery.txt

LICENSE
Copyright (c) 2010, Samuel Mendes
All rights reserved.
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:
  • Redistributions of source code must retain the above copyright
notice, this list of conditions and the following disclaimer.
  • Redistributions in binary form must reproduce the above copyright
notice, this list of conditions and the following disclaimer in the
documentation and/or other materials provided with the distribution.
  • Neither the name of ᐱ nor the names of its
contributors may be used to endorse or promote products derived
from this software without specific prior written permission.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
"AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED
TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
Samuel Mendes samuel.mendes@gmail.com
About
A Cocoa framework implementing a bayesian classifier
Resources
Readme
BSD-3-Clause license
Activity
Stars
69 stars
Watchers
6 watching
Forks
4 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
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try {
var __m = "youtube.com";
var __re = new RegExp('^' + "youtube\\.com" + '
GitHub - lok/BayesianKit: A Cocoa framework implementing a bayesian classifier · GitHub
Skip to content
BranchesTags
Repository files navigation
BayesianKit - Cocoa Objective-C Framework for a naive bayesian classifier
BayesianKit is a Mac OS X Framework written by Samuel Mendes in Objective-C 2.0
and released under BSD 3-clauses license. BayesianKit offers a simple, ready to
use, implementation for a bayesian classifier. A command line utility is also
provided.
Dependencies
  • ParseKit used for the default tokenizer
  • appledoc used to generate the
headers' documentation
Both of them are included as submodules. After having cloned the repository
type:
git submodule init
git submodule update

However appledoc needs Doxygen which is
not provided.
Xcode Project
The BayesianKit project consists of 3 targets:
  • BayesianKit : The BayesianKit framework.
  • Bayes : The command line utility.
  • Install Documentation : The script running appledoc.
BayesianKit usage
The default classifier comes with a tokenizer based on ParseKit. Quite efficient
when training on source code. It also implements and use the Robinson-Fisher
combiner on probabilities. Both the tokenizer and combiner can be changed,
however note that they are not saved along the training. Hence if you load a
classifier from a file, you must reset the tokenizer and/or combiner.
Creating and Training a new classifier
BKClassifier *classifier = [[BKClassifier alloc] init];
[classifier trainWithString:@"one two three four five"
forPoolNamed:@"english"];
[classifier trainWithString:@"un deux trois quatre cinq"
forPoolNamed:@"french"];

Saving and reloading the training data
[classifier writeToFile:@"counting.bks"]
// Another day, in a different process
BKClassifier *anotherOne;
anotherOne = [BKClassifier classifierWithContentsOfFile:@"counting.bks"];

Using the classifier to make a guess
NSDictionary *results = [anotherOne guessWithString:@"three platypuses"];
NSLog(@"%@", results);

The output is:
$ {
english = "0.9999";
}

Bayes
This tool was intended to test quickly the classifier, and works only with
files. A manpage is also provided with every details.
Installation
From the root directory of the project:
sudo cp build/Release/bayes /usr/local/bin/
sudo cp docs/man/man1/bayes.1 /usr/local/share/man/man1/

Training with a save file
bayes -f save.bks -s -t english shakespeare.txt -t french moliere.txt

Guessing based on this training
bayes -f save.bks -g mystery.txt

LICENSE
Copyright (c) 2010, Samuel Mendes
All rights reserved.
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:
  • Redistributions of source code must retain the above copyright
notice, this list of conditions and the following disclaimer.
  • Redistributions in binary form must reproduce the above copyright
notice, this list of conditions and the following disclaimer in the
documentation and/or other materials provided with the distribution.
  • Neither the name of ᐱ nor the names of its
contributors may be used to endorse or promote products derived
from this software without specific prior written permission.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
"AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED
TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
Samuel Mendes samuel.mendes@gmail.com
About
A Cocoa framework implementing a bayesian classifier
Resources
Readme
BSD-3-Clause license
Activity
Stars
69 stars
Watchers
6 watching
Forks
4 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
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try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '
GitHub - lok/BayesianKit: A Cocoa framework implementing a bayesian classifier · GitHub
Skip to content
BranchesTags
Repository files navigation
BayesianKit - Cocoa Objective-C Framework for a naive bayesian classifier
BayesianKit is a Mac OS X Framework written by Samuel Mendes in Objective-C 2.0
and released under BSD 3-clauses license. BayesianKit offers a simple, ready to
use, implementation for a bayesian classifier. A command line utility is also
provided.
Dependencies
  • ParseKit used for the default tokenizer
  • appledoc used to generate the
headers' documentation
Both of them are included as submodules. After having cloned the repository
type:
git submodule init
git submodule update

However appledoc needs Doxygen which is
not provided.
Xcode Project
The BayesianKit project consists of 3 targets:
  • BayesianKit : The BayesianKit framework.
  • Bayes : The command line utility.
  • Install Documentation : The script running appledoc.
BayesianKit usage
The default classifier comes with a tokenizer based on ParseKit. Quite efficient
when training on source code. It also implements and use the Robinson-Fisher
combiner on probabilities. Both the tokenizer and combiner can be changed,
however note that they are not saved along the training. Hence if you load a
classifier from a file, you must reset the tokenizer and/or combiner.
Creating and Training a new classifier
BKClassifier *classifier = [[BKClassifier alloc] init];
[classifier trainWithString:@"one two three four five"
forPoolNamed:@"english"];
[classifier trainWithString:@"un deux trois quatre cinq"
forPoolNamed:@"french"];

Saving and reloading the training data
[classifier writeToFile:@"counting.bks"]
// Another day, in a different process
BKClassifier *anotherOne;
anotherOne = [BKClassifier classifierWithContentsOfFile:@"counting.bks"];

Using the classifier to make a guess
NSDictionary *results = [anotherOne guessWithString:@"three platypuses"];
NSLog(@"%@", results);

The output is:
$ {
english = "0.9999";
}

Bayes
This tool was intended to test quickly the classifier, and works only with
files. A manpage is also provided with every details.
Installation
From the root directory of the project:
sudo cp build/Release/bayes /usr/local/bin/
sudo cp docs/man/man1/bayes.1 /usr/local/share/man/man1/

Training with a save file
bayes -f save.bks -s -t english shakespeare.txt -t french moliere.txt

Guessing based on this training
bayes -f save.bks -g mystery.txt

LICENSE
Copyright (c) 2010, Samuel Mendes
All rights reserved.
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:
  • Redistributions of source code must retain the above copyright
notice, this list of conditions and the following disclaimer.
  • Redistributions in binary form must reproduce the above copyright
notice, this list of conditions and the following disclaimer in the
documentation and/or other materials provided with the distribution.
  • Neither the name of ᐱ nor the names of its
contributors may be used to endorse or promote products derived
from this software without specific prior written permission.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
"AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED
TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
Samuel Mendes samuel.mendes@gmail.com
About
A Cocoa framework implementing a bayesian classifier
Resources
Readme
BSD-3-Clause license
Activity
Stars
69 stars
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6 watching
Forks
4 forks
Report repository
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try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '
GitHub - lok/BayesianKit: A Cocoa framework implementing a bayesian classifier · GitHub
Skip to content
BranchesTags
Repository files navigation
BayesianKit - Cocoa Objective-C Framework for a naive bayesian classifier
BayesianKit is a Mac OS X Framework written by Samuel Mendes in Objective-C 2.0
and released under BSD 3-clauses license. BayesianKit offers a simple, ready to
use, implementation for a bayesian classifier. A command line utility is also
provided.
Dependencies
  • ParseKit used for the default tokenizer
  • appledoc used to generate the
headers' documentation
Both of them are included as submodules. After having cloned the repository
type:
git submodule init
git submodule update

However appledoc needs Doxygen which is
not provided.
Xcode Project
The BayesianKit project consists of 3 targets:
  • BayesianKit : The BayesianKit framework.
  • Bayes : The command line utility.
  • Install Documentation : The script running appledoc.
BayesianKit usage
The default classifier comes with a tokenizer based on ParseKit. Quite efficient
when training on source code. It also implements and use the Robinson-Fisher
combiner on probabilities. Both the tokenizer and combiner can be changed,
however note that they are not saved along the training. Hence if you load a
classifier from a file, you must reset the tokenizer and/or combiner.
Creating and Training a new classifier
BKClassifier *classifier = [[BKClassifier alloc] init];
[classifier trainWithString:@"one two three four five"
forPoolNamed:@"english"];
[classifier trainWithString:@"un deux trois quatre cinq"
forPoolNamed:@"french"];

Saving and reloading the training data
[classifier writeToFile:@"counting.bks"]
// Another day, in a different process
BKClassifier *anotherOne;
anotherOne = [BKClassifier classifierWithContentsOfFile:@"counting.bks"];

Using the classifier to make a guess
NSDictionary *results = [anotherOne guessWithString:@"three platypuses"];
NSLog(@"%@", results);

The output is:
$ {
english = "0.9999";
}

Bayes
This tool was intended to test quickly the classifier, and works only with
files. A manpage is also provided with every details.
Installation
From the root directory of the project:
sudo cp build/Release/bayes /usr/local/bin/
sudo cp docs/man/man1/bayes.1 /usr/local/share/man/man1/

Training with a save file
bayes -f save.bks -s -t english shakespeare.txt -t french moliere.txt

Guessing based on this training
bayes -f save.bks -g mystery.txt

LICENSE
Copyright (c) 2010, Samuel Mendes
All rights reserved.
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:
  • Redistributions of source code must retain the above copyright
notice, this list of conditions and the following disclaimer.
  • Redistributions in binary form must reproduce the above copyright
notice, this list of conditions and the following disclaimer in the
documentation and/or other materials provided with the distribution.
  • Neither the name of ᐱ nor the names of its
contributors may be used to endorse or promote products derived
from this software without specific prior written permission.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
"AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED
TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
Samuel Mendes samuel.mendes@gmail.com
About
A Cocoa framework implementing a bayesian classifier
Resources
Readme
BSD-3-Clause license
Activity
Stars
69 stars
Watchers
6 watching
Forks
4 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
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function applyDarkMode() {
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filter: invert(1) hue-rotate(180deg) !important;
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[data-theme="light"], [data-theme="light"],
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if (e.altKey && e.shiftKey && e.key === 'D') {
e.preventDefault();
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applyDarkMode();
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applyDarkMode();
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if (enabled && !document.getElementById('universal-dark-mode-style')) {
applyDarkMode();
}
});
observer.observe(document.head, { childList: true });
console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');
})();
}
} catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); }
})();
})();
GitHub - lok/BayesianKit: A Cocoa framework implementing a bayesian classifier · GitHub
Skip to content
BranchesTags
Repository files navigation
BayesianKit - Cocoa Objective-C Framework for a naive bayesian classifier
BayesianKit is a Mac OS X Framework written by Samuel Mendes in Objective-C 2.0
and released under BSD 3-clauses license. BayesianKit offers a simple, ready to
use, implementation for a bayesian classifier. A command line utility is also
provided.
Dependencies
  • ParseKit used for the default tokenizer
  • appledoc used to generate the
headers' documentation
Both of them are included as submodules. After having cloned the repository
type:
git submodule init
git submodule update

However appledoc needs Doxygen which is
not provided.
Xcode Project
The BayesianKit project consists of 3 targets:
  • BayesianKit : The BayesianKit framework.
  • Bayes : The command line utility.
  • Install Documentation : The script running appledoc.
BayesianKit usage
The default classifier comes with a tokenizer based on ParseKit. Quite efficient
when training on source code. It also implements and use the Robinson-Fisher
combiner on probabilities. Both the tokenizer and combiner can be changed,
however note that they are not saved along the training. Hence if you load a
classifier from a file, you must reset the tokenizer and/or combiner.
Creating and Training a new classifier
BKClassifier *classifier = [[BKClassifier alloc] init];
[classifier trainWithString:@"one two three four five"
forPoolNamed:@"english"];
[classifier trainWithString:@"un deux trois quatre cinq"
forPoolNamed:@"french"];

Saving and reloading the training data
[classifier writeToFile:@"counting.bks"]
// Another day, in a different process
BKClassifier *anotherOne;
anotherOne = [BKClassifier classifierWithContentsOfFile:@"counting.bks"];

Using the classifier to make a guess
NSDictionary *results = [anotherOne guessWithString:@"three platypuses"];
NSLog(@"%@", results);

The output is:
$ {
english = "0.9999";
}

Bayes
This tool was intended to test quickly the classifier, and works only with
files. A manpage is also provided with every details.
Installation
From the root directory of the project:
sudo cp build/Release/bayes /usr/local/bin/
sudo cp docs/man/man1/bayes.1 /usr/local/share/man/man1/

Training with a save file
bayes -f save.bks -s -t english shakespeare.txt -t french moliere.txt

Guessing based on this training
bayes -f save.bks -g mystery.txt

LICENSE
Copyright (c) 2010, Samuel Mendes
All rights reserved.
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:
  • Redistributions of source code must retain the above copyright
notice, this list of conditions and the following disclaimer.
  • Redistributions in binary form must reproduce the above copyright
notice, this list of conditions and the following disclaimer in the
documentation and/or other materials provided with the distribution.
  • Neither the name of ᐱ nor the names of its
contributors may be used to endorse or promote products derived
from this software without specific prior written permission.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
"AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED
TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
Samuel Mendes samuel.mendes@gmail.com
About
A Cocoa framework implementing a bayesian classifier
Resources
Readme
BSD-3-Clause license
Activity
Stars
69 stars
Watchers
6 watching
Forks
4 forks
Report repository
Releases
Packages
Contributors
Languages