Post by account_disabled on Dec 7, 2023 3:24:31 GMT
This is a functionality that is highly desired by business users although in my opinion it still requires some refinement to make the presented results more understandable to users. The presented Smart Discovery tool is not the last functionality that SAC has to offer in the field of Augmented Analytics. Once we verify patterns in historical data SAC can help us look into the future using Smart Predict functionality. SAC predictive models As part of its predictive services SAC offers three types of predictive models Classification used when the tested variable can have binary values. For example we may try to predict whether a customer will make a purchase truefalse based on available customer characteristics.
Regression the application of this model is the prediction of a numerical value based on the diagnosed correlation between descriptive variables and the variable under study. Using this type of model we can identify the descriptive variables that have the greatest impact on Email Marketing List the outcome variable of interest and assess the potential numerical value of the variable of interest for a hypothetical combination of descriptive variables. Time series is nothing more than a time series forecast based on historical data For each type of model the operation pattern is similar User Preparation of historical data file or connection to a database Data import to the platform User Indication of the column with the tested variable Defining a filter for explanatory variables.
SAC Division of the provided data into a training and verification set Generating several prediction models and selecting the best one based on comparing the results with the verification set User Analysis of model parameters Accuarcy Predictive Power Building reports in SAC using model results When assessing the functionalities of SAC in the field of data prediction it can be concluded that their main advantage is the simplicity of use which allows you to perform complex analysis without the need to have advanced statistical knowledge.
Regression the application of this model is the prediction of a numerical value based on the diagnosed correlation between descriptive variables and the variable under study. Using this type of model we can identify the descriptive variables that have the greatest impact on Email Marketing List the outcome variable of interest and assess the potential numerical value of the variable of interest for a hypothetical combination of descriptive variables. Time series is nothing more than a time series forecast based on historical data For each type of model the operation pattern is similar User Preparation of historical data file or connection to a database Data import to the platform User Indication of the column with the tested variable Defining a filter for explanatory variables.
SAC Division of the provided data into a training and verification set Generating several prediction models and selecting the best one based on comparing the results with the verification set User Analysis of model parameters Accuarcy Predictive Power Building reports in SAC using model results When assessing the functionalities of SAC in the field of data prediction it can be concluded that their main advantage is the simplicity of use which allows you to perform complex analysis without the need to have advanced statistical knowledge.