Sentence examples for data classification techniques from inspiring English sources

Traditional data classification techniques usually divide the data space into sub-spaces, each representing a class.

Due to the vast number of applications, many data classification techniques have been developed.

Probabilistic neural network (PNN) and k-Nearest Neighbors (k-NN) methods are widely used data classification techniques.

The static data classification techniques cannot be used in processing data streams due to four challenges [1 3].

Regular data classification techniques are based mainly on two strong assumptions: (1) the existence of a reasonably large labeled set of data to be used in training; and (2) future input data instances conform to the distribution of the training set, i.e. data distribution is stationary along time.

The literature on GPS data classification techniques largely comes from the travel behavior and physical activity research fields.

The HCA is a data classification technique.

The data classification technique traditionally performs well at avoiding overfitting of training data [4].

The HCA is a group of data classification technique; there are different clustering techniques; however, the hierarchical clustering is the one most widely useful in earth sciences (Davis 2002).

Therefore, due to its reliability, consistency and robustness in mask estimation ability over a range of acoustic environments, the FCM algorithm is deduced as the most suitable data classification technique out of the three evaluated in this study for the purposes of mask estimation in this BSS framework.

Discriminant analysis, a data classification technique, is a procedure that uses information on several variables and predicts the group to which a subject belongs based on those variables.