"is the feature vector" is a correct and usable phrase in written English.
You can use it to describe data used in machine learning and other algorithms, such as a collection of numerical properties used to describe objects or events. For example, "The feature vector for this image classification task consists of 30 variables."
where v j is the feature vector derived from spectrum harmonics coefficients defined in (18).
w denotes the weight vector, y i the label of instance i, and x is the feature vector.
The classification process is implemented using Eq. 9, where X is the feature vector associated with the unknown (to be classified) non-ferrous material.
The feature vector for an image pair a−b in each set of experiment consists of s q r t|f(a)−f(b)|, where f(a) is the feature vector from image a and f(b) is the feature vector from image b.
It means that on the basis of a group of predefined keywords, we compute weights of the words in the text by certain methods and then form a digital vector, which is the feature vector of the text [10].
We can concatenate all GMM mean vectors to one mean supervector m of dimension C F×1 where F is the feature vector length: m = m 1 T, m 2 T, …, m C T T. (4).
The free energy (4) is a linear function of the parameters h where is the features vector.
Let x j, j=1,2,…,N be the feature vector of training set extracted from chroma-like channel with coefficient.
Suppose x*, C*, and * are the feature vector extracted from the retrieved audio content, adversary's codebook, and adversary's hidden message, respectively.
where F i, μσ PO and F j, μσ PO are the feature vector of query image (ith image of the database) and the training image (the feature vector of the jth database image), respectively.
Note that the closest point on the boundary of the polytope need not be the feature vector of a structure.
