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Isomap is used for computing a quasi-isometric, low-dimensional embedding of a set of high-dimensional data points. The algorithm provides a simple method for estimating the intrinsic geometry of a data manifold based on a rough estimate of each data point’s neighbors on the manifold. Isomap is highly efficient and generally applicable to a ...
The emgr framework is a compact open source toolbox for gramian-based model reduction and compatible with OCTAVE and MATLAB. KerMor: An object-oriented MATLAB© library providing routines for model order reduction of nonlinear dynamical systems. Reduction can be achieved via subspace projection and approximation of nonlinearities via kernels ...
In statistics, shrinkage is the reduction in the effects of sampling variation. In regression analysis, a fitted relationship appears to perform less well on a new data set than on the data set used for fitting. [1]
The process of feature selection aims to find a suitable subset of the input variables (features, or attributes) for the task at hand.The three strategies are: the filter strategy (e.g., information gain), the wrapper strategy (e.g., accuracy-guided search), and the embedded strategy (features are added or removed while building the model based on prediction errors).
Topological map matching aligns GPS points with a road network by considering the connectivity and relationships between road segments. It accounts for the structure of the network, path constraints, and the sequence of GPS points to provide accurate and realistic route matching, especially in complex environments.
MapReduce is a programming model and an associated implementation for processing and generating big data sets with a parallel and distributed algorithm on a cluster. [1] [2] [3]A MapReduce program is composed of a map procedure, which performs filtering and sorting (such as sorting students by first name into queues, one queue for each name), and a reduce method, which performs a summary ...
Data compression aims to reduce the size of data files, enhancing storage efficiency and speeding up data transmission. K-means clustering, an unsupervised machine learning algorithm, is employed to partition a dataset into a specified number of clusters, k, each represented by the centroid of its points. This process condenses extensive ...
This example illustrates the implementation of the dynamic time warping algorithm when the two sequences s and t are strings of discrete symbols. For two symbols x and y, d(x, y) is a distance between the symbols, e.g. d(x, y) = | |.