International Journal For Multidisciplinary Research

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Everything Everywhere All At Once

Author(s) T. Joshua, S. Madhan, S.V. Girivasan, A. Meenakshi
Country India
Abstract In the era of big data, where vast amounts of information are constantly generated and stored, the ability to efficiently
navigate through these datasets and extract meaningful insights has become increasingly crucial. This process, known
as data reduction, involves techniques for filtering and condensing large datasets to identify the most relevant and
informative data points. By reducing the dimensionality of the data, data reduction facilitates further analysis,
interpretation, and visualization, enabling researchers and analysts to gain a deeper understanding of the underlying
patterns and trends within the data. One of the primary objectives of data reduction is to improve the effectiveness of
basic or fundamental searches. By identifying the data that is most pertinent to these searches, data reduction
techniques can significantly enhance the precision and recall of search results. This is particularly valuable in
situations where the search criteria are broad or ambiguous, as data reduction can help to narrow down the search
space and focus on the most relevant data points. Data reduction techniques can be broadly categorized into two main
types: feature selection and dimensionality reduction. Feature selection methods involve identifying and selecting the
most relevant subset of features from the original dataset. This process can be performed using various techniques,
such as correlation analysis, filter methods, and wrapper methods. Dimensionality reduction techniques, on the other
hand, transform the data into a lower-dimensional representation while preserving as much of the original
information as possible.
Keywords Visualization, Data reduction technique, Dimensionality reduction
Field Engineering
Published In Volume 6, Issue 2, March-April 2024
Published On 2024-04-04
Cite This Everything Everywhere All At Once - T. Joshua, S. Madhan, S.V. Girivasan, A. Meenakshi - IJFMR Volume 6, Issue 2, March-April 2024. DOI 10.36948/ijfmr.2024.v06i02.15991
DOI https://doi.org/10.36948/ijfmr.2024.v06i02.15991
Short DOI https://doi.org/gtp8m9
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