Natural Language Processing with PythonWe can use natural language processing to make predictions.
Example: Given a product review, a computer can predict if its positive or negative based on the text.
In this article you will learn how to make a prediction program based on natural language processing.
Related course: Natural Language Processing with Python
nlp prediction example
Given a name, the classifier will predict if it’s a male or female.
To create our analysis program, we have several steps:
- Data preparation
- Feature extraction
The first step is to prepare data.
We use the names set included with nltk.
This dataset is simply a collection of tuples. To give you an idea of what the dataset looks like:
You can define your own set of tuples if you wish, its simply a list containing many tuples.
Based on the dataset, we prepare our feature. The feature we will use is the last letter of a name:
We define a featureset using:
and the features (last letters) are extracted using:
Training and prediction
We train and predict using:
A classifier has a training and a test phrase.
If you want to give the name during runtime, change the last line to:
For Python 2, use raw_input.