TheReduce DimensionalityLive Editor task enables you to interactively perform Principal Component Analysis (PCA). The task generates MATLAB®code for your live script and returns the resulting transformed data to the MATLAB workspace. Using theReduce DimensionalityLive Editor task, you can: ...
Truncated Singular Value Decomposition (SVD) is a matrix factorization technique that factors a matrix M into the three matrices U, Σ, and V. This is very similar to PCA, excepting that the factorization for SVD is done on the data matrix, whereas for PCA, the factorization is done on th...
Dimensionality reductionFeature extractionCommodity hardwarePythonHyperspectral image classificationLocal Fisher Discriminant Analysis (LFDA) is a supervised feature extraction technique that proved to be efficient in reducing several types of data. However, it depends on the number of samples per class in a...
Therefore, this study presents a multivariate application of the normal boundary intersection (NBI) method to reduce dimensionality in optimization problems of the LBM process. Such an approach is capable of exploring the entire solution space with only a small number of Pareto points, and generating...
I have a large data set on the form of a data.frame. I want to apply a function that works using subsets of the data.frame without the need for communication between the chunks, and I want to apply the function fast. In other words, I can safely split the matrix and speed the comp...
Hadoop can be fed data either from disk or fromHDFS. In case of Amazon EMR though we will have to upload those two files to Amazon’s Simple Storage Service (S3). For that purpose you enter theS3 sectionof your AWS console and create a bucket. The bucket needs a globally (also this...
The Reduce Dimensionality Live Editor task enables you to interactively perform Principal Component Analysis (PCA). The task generates MATLAB® code for your live script and returns the resulting transformed data to the MATLAB workspace. Using the Reduce Dimensionality Live Editor task, you can: Det...
The data scientist can reduce the dimensionality using feature selection, feature extraction, and type transforma- tion (Aggarwal 2015; Sorzano et al. 2014). Prominent dimensionality reduction techniques include singular value decomposition (SVD), principal component analysis (PCA), and simple random ...
One key limiting factor for automated text classification is memory consumption. As you accumulate more news articles, bills, and legal opinions, the term-document matrices used to represent the data grow quickly. RTextTools provides two algorithms, support vector machines and maximum entropy, that ...