# Naive Bayes In Python

2018-08-09

### Naive Bayes in the Industry

Now that you have an idea of what exactly Naive Bayes is and how it works, let’s see where it is used in the industry.

Our first industrial use case is News Categorization, or we can use the term ‘text classification’ to broaden the spectrum of this algorithm. News on the web is rapidly growing where each news site has its own different layout and categorization for grouping news. Companies use a web crawler to extract useful text from HTML pages of news articles to construct a Full Text RSS. The contents of each news article is tokenized (categorized). In order to achieve better classification results, we remove the less significant words, i.e. stop, from the document. We apply the naive Bayes classifier for classification of news content based on news code.

It’s a good overview of the topic and a particular implementation in Python.  Naive Bayes is a technique which you want in the bag:  there are a lot of techniques which tend to be better in specific domains, but Naive Bayes is easy to implement and usually provides acceptable performance.

## Dealing With Multicollinearity With R

2018-08-21

Chaitanya Sagar explains the concept of multicollinearity in linear regressions and how we can mitigate this issue in R: Perfect multicollinearity occurs when one independent variable is an exact linear combination of other variables. For example, you already have X and Y as independent variables and you add another variable, Z = a*X + b*Y, […]

## Performing Linear Regression With Power BI

2018-08-16

Jason Cantrell shows how to create a simple linear regression in Power BI: Linear Regression is a very useful statistical tool that helps us understand the relationship between variables and the effects they have on each other. It can be used across many industries in a variety of ways – from spurring value to gaining […]

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August 2018
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