Examples of 'feature space' in a sentence
Meaning of "feature space"
feature space: In mathematics and computer science, a feature space refers to the space in which each observation in a dataset is represented by a vector of features or characteristics. It is commonly used in machine learning and data analysis
How to use "feature space" in a sentence
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feature space
There is a body of films that feature space stations.
The current feature space is removed from the database.
The training examples are mapped into multidimensional feature space.
Then each point in the feature space is labelled with certain rank by ranking method.
The set of all possible feature vectors constitutes a feature space.
A Gaussian mixture model was fit on the feature space with one Gaussian component per material.
A neural network without residual parts explores more of the feature space.
HV feature space.
The comparison of document maps from feature space to distance space.
The network then gradually restores the skipped layers as it learns the feature space.
They attempt to maximize the margin in feature space between two classes.
This method allows classifying objects based on closest training examples in the feature space.
Said feature space comprises an existing feature vector ;.
Any known classification technique in multidimensional feature space might be used.
Said feature space comprises an existing feature vector ; and step ( b ) further comprises the steps of,.
See also
The vector space associated with these vectors is often called the feature space.
Fig . 2 shows a graphical depiction of an exemplary 2-dimensional feature space populated with eight 2-dimensional neurons.
In both cases, the input consists of the k closest training examples in the feature space.
As an example of this last point, consider the feature space shown to the right.
This allows the algorithm to fit the maximum-margin hyperplane in a transformed feature space.
Within a support vector machine, the dimensionally of the feature space may be very high.
A single-instance algorithm can then be applied to learn the concept in this new feature space.
This eliminates the need for a calibration between the feature space and the robot 's workspace.
In the other words, the SFS-algorithm performs greedy optimization in the feature space.
As a kernel, K corresponds to an inner product in a feature space based on some mapping φ,.
Furthermore, neurons may overlap one another in feature space.
The final two half-hour shows only feature Space Ghost.
The feature distances may be expressed, for example, using Euclidean distance in the feature space.
The second type of space is semi-fixed feature space.
In a preferred embodiment, the neurons are hyper-ellipses in the k - dimensional feature space.
Within a support vector machine, the dimensionally of the feature space may be huge.
Generally, the above-mentioned features are not sufficient for discriminating a complex feature space uniquely.
Automatic seizure detection using a two-dimensional EEG feature space.
The feature vector F represents a point in the k - dimensional feature space.
For purposes of this specification, the term " feature vector " refers to a point in feature space.
In this case we call F { \ displaystyle F } the feature space.
