Isometric feature Mapping (Isomap) gives promising results in preserving the original manifold structure in the case of a highly twisted and curved manifold. Classical Multi-Dimensional Scaling (MDS) uses Euclidean distance concept for obtaining low-dimensional embedding. As a distance preserving dimensionality reduction technique, Isomap gives emphasis on geodetic distances. Due to lack of any linear relationship between reduced embedded information and original high-dimensional information, it is considered a nonlinear dimensionality reduction technique. This paper concentrates on multi-class manifold geometry preservation. Like MDS, Sammon’s mapping tries to preserve the manifold geometry by minimizing the Sammon’s stress. Sammon’s projection gives better result in preserving small distances. Sammon’s algorithm was applied instead of MDS for embedding information in a lower dimension in the final step of Isomap and a more clear output was obtained.

Increase in the size of datasets creates new challenges in data analysis. So, reducing the dimension of data is the most important requirement of the current era. Dimension of data is the number of variables or attributes for which we take observations. Generally, all the variables that we measure are not important for understanding a specific phenomenon. So, according to our requirement, we can reduce the dimension of datasets by considering only the important variables for our requirement.

Data reduction techniques try to preserve the integrity of the data. Dimensionality reduction is one type of data reduction. Feature selection technique reduces the original data keeping as much original information as possible and is used both for data reduction and visualization process. The aim of dimension reduction techniques is to solve the problem of curse of dimensionality of high-dimensional spaces.

One of the important problems in dimension reduction is to visualize the data after converting to a lower dimension and preserving the original geometry. The aim of visualization is to represent the information in a graphical format. During the process of embedding of original information in a lower dimension there may be the chances of loss of information. So, explicit control of information is required during the reduction process.

Computer Sciences Journal, Business Intelligence, Enterprise Systems, Enterprise Resource Planning, Customer Relationship Management, CRM, Business Operations Management, Business Process Mining, Finite State Machine, Transactional Information System, Genetic Algorithms, Decision Making Process, Data Mining Tools, Online Analysis Processing, OLAP, Artificial Intelligence.