Feature And Text Classification Using Naive Bayes In R

I wrap up my series on the Naive Bayes class of algorithms, finally writing some code along the way:

Now we’re going to look at movie reviews and predict whether a movie review is a positive or a negative review based on its words. If you want to play along at home, grab the data set, which is under 3MB zipped in 2000 reviews in total.

Unike last time, I’m going to break this out into sections with commentary in between. If you want the full script with notebook, check out the GitHub repo I put together for this talk.

Assuming I ever get a chance to do this talk again, I’m probably going to change the data sets in the example given how overplayed iris is.

Related Posts

Building an Image Classifier with PyTorch

Rogier van der Geer shows how you can use PyTorch to build out a Convolutional Neural Network for image classification: The tool that we are going to use to make a classifier is called a convolutional neural network, or CNN. You can find a great explanation of what these are right here on wikipedia. But we […]

Read More

xgboost and Small Numbers of Subtrees

John Mount covers an interesting issue you can run into when using xgboost: While reading Dr. Nina Zumel’s excellent note on bias in common ensemble methods, I ran the examples to see the effects she described (and I think it is very important that she is establishing the issue, prior to discussing mitigation).In doing that I ran into one more […]

Read More

Categories

January 2019
MTWTFSS
« Dec Feb »
 123456
78910111213
14151617181920
21222324252627
28293031