G2M Insights

Frequently asked questions about the G2M platform

This post discussed how data is encoded and protected in the G2M platform when building a machine learning model

How is my data encoded?

This post discusses which security mode you should choose in the G2M platform when building a machine learning model

Which security mode should I choose?

This post provides a guide on how do I create a new dataset in the G2M platform prior to building a new machine learning model.

How do I create a new dataset?

Instructions on how do I delete an existing dataset in the G2M platform.

How do I delete an existing dataset?

This article discusses what type of data sources you can use when creating a machine learning model in the G2M platform.

What type of data sources can I use?

This article discusses how you can change your dataset metadata settings and configuration in the G2M platform

How do I change my dataset settings?

This article discusses different types of datasets commonly used by business analysts to build machine learning models

What is the difference between working with a CSV file vs. a database or a data lake?

This article discusses what you should look for when exploring a dataset in the G2M platform

What should I look for when exploring a dataset?

Lists G2M Platform IP address range for access control or whitelisting configuration

G2M Platform IP Addresses

Discusses the methodology used to identify which variables are most predictive

How are variable predictors computed?

Frequently asked questions regarding data management in the G2M platform

Data Management FAQ

Frequently asked questions regarding the use of machine learning models in the G2M platform

Modeling FAQ

This article discusses what types of machine learning models you can build with the the G2M platform.

What types of models can I build with the G2M platform?

This article discusses how do I create a new model object in the G2M platform?

How do I create a new model?

This article discusses what variables you should select when building a machine learning model in the G2M platform.

What variables should I select?

Provides a reference to lists and descriptions of algorithms by category: propensity, clustering, regression, A/B testing

Which algorithm should I pick?

This article discusses which algorithm you should pick when building an A/B testing model in the G2M platform.

Which algorithm should I pick for my A/B testing analysis?

Which algorithm should I pick for my marketing mix model?

What is the estimated sample size?

When should I downsample my dataset?

This article discusses training size when training a machine learning model.

What dataset training size should I use?

This article discussed what machine learning model drift is and how to deal with it.

What is model drift?

This article briefly discusses how to delete an existing machine learning model in the G2M platform?

How do I delete an existing model?

This article discusses how to share a machine learning model with another user in the G2M platform

How do I share a model with another user?

This article briefly discusses what the predict stage of a model is in the G2M platform

What is the predict stage of a model?

This article discusses how to make predictions using an existing model in the G2M platform

How can I make predictions using an existing model?

This article discusses how to export predictions you just generated in the G2M platform

How can I export predictions I just generated?

How do I interpret error metrics for my marketing mix model?

This article discusses how the G2M platform removes outliers then the outlier removal option is selected

What is outlier removal?

How can I export my training results to a presentation?

How can I convert my G2M model to a Jupyter notebook?

How can I export my prediction results to a spreadsheet?

How can I duplicate a model?

How is prediction performance monitored?

What is the Infer stage of a model

What is MARK?

Hyper Tuning optimizes machine learning hyperparameters to improve accuracy, efficiency, and prevent overfitting using search techniques.

What is Hyper Tuning?

General Modeling FAQ

This article discusses which algorithm you should pick when building a clustering model in the G2M platform.

Which algorithm should I pick for my clustering model?

This article discusses how the G2M platform optimizes the number of clusters when clustering a dataset

How does G2M optimize the number of clusters when clustering a dataset?

This article discusses how to interpret error metrics for your clustering model in the G2M platform

How do I interpret error metrics for my clustering model?

Clustering FAQ

Provides a list of algorithms with a brief summary for each of the main machine learning algorithms used for propensity modeling

Which algorithm should I pick for my propensity model?

This article briefly discusses what SMOTE preprocessing is.

What is SMOTE preprocessing?

How do I interpret driver rankings for my propensity or regression model?

This article discusses how to interpret error metrics when building a propensity model in the G2M platform

How do I interpret error metrics for my propensity model?

This article briefly discusses what a confusion matrix is

What is a confusion matrix?

This article briefly discusses what an ROC curve is

What is an ROC curve?

This article discusses how to interpret the propensity bin comparison chart when running a propensity model in the G2M platform

How do I interpret the propensity bin comparison chart?

How is prediction performance monitored for my propensity model?

Propensity Scoring FAQ

This article discusses which algorithm you should pick when building a machine learning regression model in the G2M platform.

Which algorithm should I pick for my regression model?

This article discusses how to interpret error metrics for your regression model in the G2M platform

How do I interpret error metrics for my regression model?

How do I interpret coefficients for my regression model?

How do I interpret lag estimates for my regression model?

How do I interpret saturation estimates for my regression model?

How is prediction performance monitored for my regression model?

Regression Analysis FAQ

What are treatment effects?

What are unadjusted impacts when performing A/B testing analysis?

What are matched propensity distributions?

How do I interpret the variance waterfall with A/B testing?

What is refutation in A/B testing?

A/B Testing Analysis FAQ

How do I interpret marketing mix attribution results?

How do I interpret media attribution trended over time?

What are media response curves?

The Optimization page shows how your predicted results change when the model reallocates budget across channels to maximize your selected KPI. By default, the model performs optimization on the last…

How do I interpret the optimization results for my media mix model?

Marketing Mix Modeling FAQ

Detailed description of which metrics are shown in the Analytics Engine status widget in the G2M platform

Which metrics are shown in the Analytics Engine status widget?

How can I check on the status of my G2M model run?

How can I check on the status on my model run?

How can I upgrade or upsize my analytics engine?

Frequently asked questions regarding the use of analytics engines in the G2M platform

Analytics Engine FAQ

How can I change my email address in the G2M platform

How can I change my email address?

What analytics engines can I use in the G2M platform to run machine learning models

What analytics engines can I use?

How can I change my privacy settings in the G2M platform

How can I change my privacy settings?

Discusses number of users allowed by G2M platform service tier

How many users can I have on my team?

Frequently asked questions regarding configuration of settings in the G2M platform

Settings FAQ

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