wink-naive-bayes-text-classifier - npm Package Compare versions

Comparing version 2.1.0 to 2.2.0

.nyc_output/processinfo/index.json

@@ -1,1 +0,1 @@
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package.json

 {
   "name": "wink-naive-bayes-text-classifier",
-  "version": "2.1.0",
-  "description": "Configurable Naive Bayes Classifier for text with cross-validation support",
+  "version": "2.2.0",
+  "description": "Naive Bayes Text Classifier",
   "keywords": [
@@ -9,7 +9,8 @@ "Naive Bayes",
     "Machine Learning",
-    "Cross-validation",
     "NLP",
     "Natural Language Processing",
-    "AI",
-    "wink"
+    "Chatbot",
+    "Sentiment Analysis",
+    "winkNLP",
+    "Text Classification"
   ],
@@ -16,0 +17,0 @@ "main": "src/wink-naive-bayes-text-classifier.js",

README.md

 
 # wink-naive-bayes-text-classifier
 
-Configurable [Naive Bayes](https://en.wikipedia.org/wiki/Naive_Bayes_classifier) Classifier for text with cross-validation support
+Naive Bayes Text Classifier
 
@@ -10,11 +10,18 @@ ### [![Build Status](https://app.travis-ci.com/winkjs/wink-naive-bayes-text-classifier.svg?branch=master)](https://app.travis-ci.com/winkjs/wink-naive-bayes-text-classifier) [![Coverage Status](https://coveralls.io/repos/github/winkjs/wink-naive-bayes-text-classifier/badge.svg?branch=master)](https://coveralls.io/github/winkjs/wink-naive-bayes-text-classifier?branch=master) [![Gitter](https://img.shields.io/gitter/room/nwjs/nw.js.svg)](https://gitter.im/winkjs/Lobby)
 
-Classify text, analyse sentiments, recognize user intents for chatbot using **`wink-naive-bayes-text-classifier`**. Its [API](http://winkjs.org/wink-naive-bayes-text-classifier/NaiveBayesTextClassifier.html) offers a rich set of features:
+Classify text, analyse sentiments, recognize user intents for chatbot using **`wink-naive-bayes-text-classifier`**. Its [API](http://winkjs.org/wink-naive-bayes-text-classifier/NaiveBayesTextClassifier.html) offers a rich set of features including cross validation to compute confusion matrix, precision, and recall. It delivers impressive accuracy levels with right text pre-processing using [wink-nlp](https://www.npmjs.com/package/wink-nlp):
 
-1. Preprocess text using [wink-nlp](https://www.npmjs.com/package/wink-nlp) — tokenize, stem, remove stop words, and handle negation. It also supports [Named Entity Recognition](https://winkjs.org/wink-nlp/getting-started.html) to further enhance preprocessing. A single winkNLP based helper function for preparing text is available that (a) tokenizes, (b) removes punctuations, symbols, numerals, URLs, stop words and (c) stems. It can be required from `wink-naive-bayes-text-classifier/src/prep-text.js`.
-2. Configure **Lidstone** or **Laplace** additive smoothing.
-3. Configure **Multinomial** or **Binarized Multinomial** Naive Bayes model.
-4. Export and import learnings in JSON format that can be easily saved on hard-disk.
-5. Evaluate learning to perform n-fold cross validation.
-6. Obtain comprehensive metrics including **confusion matrix**, **precision**, and **recall**.
+| Dataset | Accuracy |
+| --- | --- |
+| **Sentiment Analysis**<br/>Amazon Product Review [Sentiment Labelled Sentences Data Set](https://archive.ics.uci.edu/ml/machine-learning-databases/00331/) at [UCI Machine Learning Repository](https://archive.ics.uci.edu/ml/index.php) | **90%** <br/> 800 training examples & 200 validation reviews<br/><br/>Refer to `sentiment-analysis-example` directory for the reference code |
+| **Intent Classification**<br/>Chatbot corpus from [NLU Evaluation Corpora](https://github.com/sebischair/NLU-Evaluation-Corpora) as mentioned in paper titled [Evaluating Natural Language Understanding Services for Conversational Question Answering Systems](https://aclanthology.org/W17-5522.pdf) | **99%** <br/>100 training examples & 106 validation<br/><br/>Refer to `chatbot-example` directory for the reference code |
 
+#### Text Pre-processing
+A [winkNLP](https://github.com/winkjs/wink-nlp) based helper function for general purpose text pre-processing is available that (a) tokenizes, (b) removes punctuations, symbols, numerals, URLs, stop words, (c) stems each token and (d) handles negations. It can be required from `wink-naive-bayes-text-classifier/src/prep-text.js`. WinkNLP's [Named Entity Recognition](https://winkjs.org/wink-nlp/getting-started.html) may be used to further enhance the pre-processing.
+
+#### Hyperparameters
+These include smoothing factor to control [additive smoothing](https://winkjs.org/wink-naive-bayes-text-classifier/NaiveBayesTextClassifier.html#defineConfig) and a [consider presence only flag](https://winkjs.org/wink-naive-bayes-text-classifier/NaiveBayesTextClassifier.html#defineConfig) to choose from Multinomial/Binarized naive bayes.
+
+The trained model can be [exported](https://winkjs.org/wink-naive-bayes-text-classifier/NaiveBayesTextClassifier.html#exportJSON) as JSON and can be [reloaded](https://winkjs.org/wink-naive-bayes-text-classifier/NaiveBayesTextClassifier.html#importJSON) later for predictions.
+
+
 ### Installation
@@ -21,0 +28,0 @@ Use [npm](https://www.npmjs.com/package/wink-naive-bayes-text-classifier) to install:

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