NEWS.md

In mskogholt/fastNaiveBayes: Extremely Fast Implementation of a Naive Bayes Classifier

fastNaiveBayes 2.2.1

Bug Fixes

• Fix bug with class prediction of a single level

fastNaiveBayes 2.2.0

New Features

• update functionality to iteratively train models
• Poisson event model

Bug Fixes

• Threshold parameter not working for gaussian

Other Changes

fastNaiveBayes 2.1.1

New Features

• load and save options

Bug Fixes

• Argument errors

fastNaiveBayes 2.1.0

New Features

• New naming structure
• User can specify priors

Bug Fixes

• y not as factor caused vague error

Other Changes

• Enriched unit tests

fastNaiveBayes 1.1.2

New Features

• threshold in all predict functions to ensure a minimum probability
• Added tweets and tweetsDTM datasets as example data and for time comparisons
• Changed Gaussian model to achieve a huge speed-up
• Removed inefficiencies for both the Bernoulli and Multinomial models. Much faster now.

Bug Fixes

• With 2x1 matrices error were thrown

Other Changes

• Removed std_threshold in Gaussian model, not necessary since the introduction of the above threshold feature
• Changed comparison to other packages in vignette

fastNaiveBayes 1.1.1

New Features

• Detect distribution. Automatically determine the distributions of a matrix for use with mixed Naive Bayes model
• A threshold for the standard deviation for the Gaussian event model. This way one can ensure that probabilities are real numbers and not NaN's due to standard deviation being 0.

Bug Fixes

Other Changes

• Expanded unit tests.
• Changed comparison to other packages in vignette
• small change to bernoulli predict function

fastNaiveBayes 1.0.1

Bug Fixes

• Fixed bug in Gaussian predict function.

Other Changes

• Changed Readme
• Changed description
• Added unit tests and Travis-ci

fastNaiveBayes 1.0.0

Initial Release of package

mskogholt/fastNaiveBayes documentation built on May 10, 2020, 6:09 p.m.