Building a model to perform regression analysis
Regression analysis within the Elastic Stack, facilitated by data frame analytics, provides a powerful means of deriving insights from complex datasets. The Elastic Stack’s advanced statistical analysis methods allow users to examine relationships between diverse data points in detail.
In data frame analytics, regression techniques are vital for estimating continuous values, such as sales figures or temperature readings, using patterns derived from historical data. With these methods, businesses and researchers can anticipate trends, discern the primary influences on outcomes, and make well-informed decisions—all in the scalable, real-time environment of the Elastic Stack.
Regression and classification are part of the supervised learning category of ML capabilities provided by the Elastic Stack, as illustrated in Figure 8.10:
Figure 8.10 – Supervised learning process overview
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