NaiveBayesClassifier | JAVA implementation of Multinomial Naive Bayes Text | Natural Language Processing library

by datumbox Java Version: Current License: GPL-3.0

X-Ray Key Features Code Snippets Community Discussions(10)Vulnerabilities Install Support

kandi X-RAY | NaiveBayesClassifier Summary

NaiveBayesClassifier is a Java library typically used in Artificial Intelligence, Natural Language Processing applications. NaiveBayesClassifier has no bugs, it has no vulnerabilities, it has a Strong Copyleft License and it has low support. However NaiveBayesClassifier build file is not available. You can download it from GitHub.

Implementation of Multinomial Naive Bayes Text Classifier.

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Support

NaiveBayesClassifier has a low active ecosystem.

It has 99 star(s) with 83 fork(s). There are 21 watchers for this library.

It had no major release in the last 6 months.

There are 1 open issues and 0 have been closed. On average issues are closed in 2323 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of NaiveBayesClassifier is current.

Quality

NaiveBayesClassifier has 0 bugs and 0 code smells.

Security

NaiveBayesClassifier has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

NaiveBayesClassifier code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

NaiveBayesClassifier is licensed under the GPL-3.0 License. This license is Strong Copyleft.

Strong Copyleft licenses enforce sharing, and you can use them when creating open source projects.

Reuse

NaiveBayesClassifier releases are not available. You will need to build from source code and install.

NaiveBayesClassifier has no build file. You will be need to create the build yourself to build the component from source.

NaiveBayesClassifier saves you 720 person hours of effort in developing the same functionality from scratch.

It has 1662 lines of code, 20 functions and 10 files.

It has medium code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

kandi has reviewed NaiveBayesClassifier and discovered the below as its top functions. This is intended to give you an instant insight into NaiveBayesClassifier implemented functionality, and help decide if they suit your requirements.

Main entry point
Trains a Bayes classifier from the given dataset
Performs a chisquare using chisquare algorithm
Predicts the category of the given text
Produces a feature stats object from a list of documents
Preprocesses a training dataset
Counts the number of occurrences of the keywords inside the text
Selects features based on a list of features
Reads all lines from a file
Tokenizes the given text
Gets the knowledgebase parameter
Set the channel critical value
Extract the keywords from a text
Removes duplicate spaces

Get all kandi verified functions for this library.

NaiveBayesClassifier Key Features

No Key Features are available at this moment for NaiveBayesClassifier.

NaiveBayesClassifier Examples and Code Snippets

No Code Snippets are available at this moment for NaiveBayesClassifier.

Community Discussions

Trending Discussions on NaiveBayesClassifier

Extracting the MAX value from a Naive Bayes Classifier

How to fix classifer and lambda to TextBlob

TextBlob error: too many values to unpack

Classifying a dataset using Naive Bayes

Issue with tokenizing words with NLTK in Python. Returning lists of single letters instead of words

Intent classification for Chatbot

How to invoke model from TensorFlow Java?

AttributeError: 'NoneType' object has no attribute 'items' for classifier = nltk.NaiveBayesClassifier.train(training_set)

UnicodeEncodeError in Python

Sentiment analysis with Lambda Expressions in Python

QUESTION

Extracting the MAX value from a Naive Bayes Classifier

Asked 2021-May-11 at 22:48

I am applying NB and NLTK to classify phrases according to some feelings, like sadness, fear, happyness etc..

classificador = nltk.NaiveBayesClassifier.train(base_completa_treinamento)

and applying this function to a phrase:

...

ANSWER

Answered 2021-May-11 at 22:48

Instead of this part:

Source https://stackoverflow.com/questions/67495135

QUESTION

How to fix classifer and lambda to TextBlob

Asked 2021-Apr-13 at 08:27

any tips are welcome. I have some nlp model and i would like create some classifer. #test

...

ANSWER

Answered 2021-Apr-13 at 08:27

With a quick search in the doc and by executing it:

blob.sentiment is not your classifier, it is the default TextBlob sentiment classifier.

In order to use your classifier you should use TextBlob(tweet,classifier=cl).classify() not TextBlob(tweet,classifier=cl).sentiment

Source https://stackoverflow.com/questions/67055391

QUESTION

TextBlob error: too many values to unpack

Asked 2021-Mar-28 at 21:38

I am trying to run the following code, but I have gotten an error that are too many values to unpack

The code is:

...

ANSWER

Answered 2021-Mar-28 at 21:38

NaiveBayesClassifier() expects a list of tuples of the form (text, label):

Source https://stackoverflow.com/questions/66846209

QUESTION

Classifying a dataset using Naive Bayes

Asked 2021-Mar-04 at 10:54

I am trying to classify a dataset of tweets using the Naive Bayes classifier found in the NLTK. However, rather than classifying a single sentence, such as below

...

ANSWER

Answered 2021-Mar-03 at 21:01

The example below will give you a generic how-to.

Creating a test dataframe

Source https://stackoverflow.com/questions/66464694

QUESTION

Issue with tokenizing words with NLTK in Python. Returning lists of single letters instead of words

Asked 2020-Jul-23 at 15:04

I'm having some trouble with my NLP python program, I am trying to create a dataset of positive and negative tweets however when I run the code it only returns what appears to be tokenized individual letters. I am new to Python and NLP so I apologise if this is basic or if I'm explaining myself poorly. I have added my code below:

...

ANSWER

Answered 2020-Jul-23 at 15:02

Your tokens are from the file name ('positive_tweets.csv'), not the data inside the file. Add a print statement like below. You will see the issue.

Source https://stackoverflow.com/questions/63055632

QUESTION

Intent classification for Chatbot

Asked 2020-Jul-19 at 02:23

I am trying to make a chatbot and to do that i have to perform two main task 1st is Intent Classification and other is Entity recognition but i stuck in Intent classification. Basically i am developing a chatbot for Ecommerce site and my chatbot have very specific use case, my chatbot has to negotiate with customers on the price of products, thats it. To keep things simple and easy i am just considering 5 intents.

Ask for price
Counter Offer
negotiation
success
Buy a product

To train a classifier on these intents i have trained a Naive Bayes classifier on my little hand written corpus of data, but that data is too too and too less to train a good classifier. I have searched on internet a lot and looked into every machine learning data repository (kaggle, uci, etc) but cannot find any data for my such specific use case. Can you guys guide me what should i do in that case. If i got a big data like i want then i will try Deep learning classifier which will far better for me. Any help would be highly appreciated.

...

ANSWER

Answered 2020-Jul-19 at 02:23

This is actually a great problem to try deep learning. As you probably already know: language models are few shot learners (https://arxiv.org/abs/2005.14165)

If you are not familiar with language model, I can explain a little bit here. Otherwise, you can skip this section. Basically, the area of NLP has got great progress by doing generative pre-training on unlabeled data. A popular example is BERT. The idea is that you can train a model on a language modeling task (e.g. next word prediction.) By training on such tasks, the model will be able to learn well the "world-knowledge". Then, when you want to use the model for other tasks, you do not need that many labeled training data. You can take a look at this video (https://www.youtube.com/watch?v=SY5PvZrJhLE) if you are interested in knowing more.

For your problem specifically, I have adapt a colab (that I prepared for my UC class) for your application: https://colab.research.google.com/drive/1dKCqwNwPCsLfLHw9KkScghBJkOrU9PAs?usp=sharing In this colab, we use a pre-trained BERT provided by Google Research, and fine-tune on your labeled data. The fine-tuning process is very fast and takes about 1 minute. The colab should work out-of-the-box for you as colab provides GPU supports to train the model. Practically, I think you many need to hand generate a more diverse set of training data, but I do not think you need to have huge data sets.

Source https://stackoverflow.com/questions/62970861

QUESTION

How to invoke model from TensorFlow Java?

Asked 2020-May-23 at 07:00

The following python code passes ["hello", "world"] into the universal sentence encoder and returns an array of floats denoting their encoded representation.

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ANSWER

Answered 2020-May-21 at 23:29

You can load TF model with Deep Java Library

Source https://stackoverflow.com/questions/61923351

QUESTION

AttributeError: 'NoneType' object has no attribute 'items' for classifier = nltk.NaiveBayesClassifier.train(training_set)

Asked 2020-Mar-23 at 15:01

I am getting this error for AttributeError: 'NoneType' object has no attribute 'items. The code is as follows:

...

ANSWER

Answered 2017-Jul-12 at 08:28

You're not returning the list from the function. In your find_feature function use:

Source https://stackoverflow.com/questions/45050805

QUESTION

UnicodeEncodeError in Python

Asked 2020-Mar-05 at 11:43

I am getting an error and I don't know what exactly I should do?! The error message:
File "pandas_libs\writers.pyx", line 55, in pandas._libs.writers.write_csv_rows UnicodeEncodeError: 'ascii' codec can't encode character u'\u2026' in position 147: ordinal not in range(128)

...

ANSWER

Answered 2020-Mar-04 at 22:54

PANDAS is tripping up on handling Unicode data, presumably in generating a CSV output file.

One approach, if you don't really need to process Unicode data, is to simply make conversions on your data to get everything ASCII.

Another approach is to make a pass on your data prior to generating the CSV output file to get the UTF-8 encoding of any non-ASCII characters. (You may need to do this at the cell level of your spreadsheet data.)

I'm assuming Python3 here...

Source https://stackoverflow.com/questions/60534921

QUESTION

Sentiment analysis with Lambda Expressions in Python

Asked 2020-Feb-18 at 15:54

I'm trying to use TextBlob to perform sentiment analysis in Power BI. I'd like to use a lamdba expression because it seems to be substantially faster than running an iterative loop in Power BI.

For example, using Text Blob:

...

ANSWER

Answered 2020-Feb-18 at 15:54

Simply

Source https://stackoverflow.com/questions/60284734

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install NaiveBayesClassifier

You can download it from GitHub.
You can use NaiveBayesClassifier 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 NaiveBayesClassifier 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 .