Feature Extraction
In this lesson, let's learn how to extract features from raw txt.
We'll cover the following...
What is feature extraction
Feature extraction is different from feature selection. Feature extraction focuses on how to extract data from complicated data, such as text or images, to numerical features. Image processing and text are complex structured data and traditional Machine Learning algorithms cannot directly process both these data types. Such data must be preprocessed to extract the corresponding features and prepare for downstream tasks. Deep Learning supports end-to-end training; for example, a neural network can process raw JPEG files without any manual processing.
The sklearn provides some functions to process the image and text, but in this lesson, we only focus on the text.
Text processing is an important field of Machine Learning algorithms. However, raw data (a sequence of tokens) can not be processed directly by models. We need to process the raw data and extract some kind of fixed size numerical feature vector for the model. We call the general process of converting the raw text documents into numerical feature ...