Schulz A, Gisbrecht A, Hammer B. Using Nonlinear Dimensionality Reduction to Visualize Classifiers. In: Rojas I, Joya G, Gabestany J, eds. Advances in computational intelligence. Proceedings. Vol 1. Lecture Notes in Computer Science. Vol 7902. Springer; 2013: 59-68
Abstract—In this paper we propose new approach in data set dimensionality reduction. We use classica...
Methods of dimensionality reduction provide a way to understand and visualize the structure of compl...
Machine learning methods are used to build models for classification and regression tasks, among oth...
Gisbrecht A, Schulz A, Hammer B. Discriminative Dimensionality Reduction for the Visualization of Cl...
Gisbrecht A, Hammer B. Data visualization by nonlinear dimensionality reduction. Wiley Interdiscipli...
The visual interpretation of data is an essential step to guide any further processing or decision m...
Schulz A, Gisbrecht A, Hammer B. Using Discriminative Dimensionality Reduction to Visualize Classifi...
Bunte K, Hammer B, Biehl M. Nonlinear dimension reduction and visualization of labeled data. In: Jia...
Schulz A, Gisbrecht A, Hammer B. Classifier inspection based on different discriminative dimensional...
Dimensionality reduction (DR) is often used as a preprocessing step in classification, but usually o...
Abstract—When performing visualization and classification, people often confront the problem of dime...
Schulz A, Brinkrolf J, Hammer B. Efficient Kernelization of Discriminative Dimensionality Reduction....
Visual analysis of high dimensional data is a challenging process. Direct visualizations work well f...
Abstract. Nonlinear dimensionality reduction (NLDR) techniques offer powerful data visualization sch...
Hammer B, Gisbrecht A, Schulz A. Applications of discriminative dimensionality reduction. In: Proce...
Abstract—In this paper we propose new approach in data set dimensionality reduction. We use classica...
Methods of dimensionality reduction provide a way to understand and visualize the structure of compl...
Machine learning methods are used to build models for classification and regression tasks, among oth...
Gisbrecht A, Schulz A, Hammer B. Discriminative Dimensionality Reduction for the Visualization of Cl...
Gisbrecht A, Hammer B. Data visualization by nonlinear dimensionality reduction. Wiley Interdiscipli...
The visual interpretation of data is an essential step to guide any further processing or decision m...
Schulz A, Gisbrecht A, Hammer B. Using Discriminative Dimensionality Reduction to Visualize Classifi...
Bunte K, Hammer B, Biehl M. Nonlinear dimension reduction and visualization of labeled data. In: Jia...
Schulz A, Gisbrecht A, Hammer B. Classifier inspection based on different discriminative dimensional...
Dimensionality reduction (DR) is often used as a preprocessing step in classification, but usually o...
Abstract—When performing visualization and classification, people often confront the problem of dime...
Schulz A, Brinkrolf J, Hammer B. Efficient Kernelization of Discriminative Dimensionality Reduction....
Visual analysis of high dimensional data is a challenging process. Direct visualizations work well f...
Abstract. Nonlinear dimensionality reduction (NLDR) techniques offer powerful data visualization sch...
Hammer B, Gisbrecht A, Schulz A. Applications of discriminative dimensionality reduction. In: Proce...
Abstract—In this paper we propose new approach in data set dimensionality reduction. We use classica...
Methods of dimensionality reduction provide a way to understand and visualize the structure of compl...
Machine learning methods are used to build models for classification and regression tasks, among oth...