The method where data values are shifted and rescaled to range between 0 and 1 is called _______.
- Data Normalization
- Data Imputation
- Data Resampling
- Data Transformation
The method of shifting and rescaling data values to range between 0 and 1 is known as "data normalization." This is commonly used in machine learning to ensure that all features have the same scale, preventing certain features from dominating others.
Loading...
Related Quiz
- A streaming platform is receiving real-time data from various IoT devices. The goal is to process this data on-the-fly and produce instantaneous analytics. Which Big Data technology is best suited for this task?
- In computer vision, detecting specific features or patterns in an image is often achieved using _______.
- What is the primary goal of Exploratory Data Analysis (EDA)?
- In a data warehouse, the _________ table is used to store aggregated data at multiple levels of granularity.
- In complex ETL processes, _________ can be used to ensure data quality and accuracy throughout the pipeline.