In machine learning, feature learning or representation learning is a set of techniques that allows a system to automatically discover the representations...

In machine learning and pattern recognition, a feature is an individual measurable property or characteristic of a phenomenon. Choosing informative, discriminating...

dictionary learning. In unsupervised feature learning, features are learned with unlabeled input data. Examples include dictionary learning, independent...

Geometric feature learning is a technique combining machine learning and computer vision to solve visual tasks. The main goal of this method is to find...

Feature engineering is a preprocessing step in supervised machine learning and statistical modeling which transforms raw data into a more effective set...

Normalization (machine learning) Normalization (statistics) Standard score fMLLR, Feature space Maximum Likelihood Linear Regression...

has been used as a feature learning (or dictionary learning) step, in either (semi-)supervised learning or unsupervised learning. The basic approach...

In statistics and machine learning, ensemble methods use multiple learning algorithms to obtain better predictive performance than could be obtained from...

for machine learning, an expert may have to apply appropriate data pre-processing, feature engineering, feature extraction, and feature selection methods...

"flexible" learning algorithm with low bias and high variance. A third issue is the dimensionality of the input space. If the input feature vectors have...