Model Explainability

Model Explainability

January 24, 2023 2023-12-30 18:15

Model Explainability

Enhance interpretability of any black-box ML model by leveraging Giggso’s evaluate and explain functionality

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Model Expalinability in Giggso

Explainability Dashboard

Dynamic explainable dashboards to evaluate and explain the model’s decisions in terms of the data used, and features contributing to its prediction behavior. Zoom into features of interest at ease with multiple user-controls and interactive visualizations.

Benefits

Increased customer satisfaction
Help customers understand why decisions were made and how their data was used to generate results, leading to increased customer satisfaction.

Increased ROI from  investments
By providing transparency into the decision-making process, this dashboard can help organizations maximize their return on investments.

Enhanced compliance with regulatory requirements

Organizations can easily be compliant with regulations such as GDPR and CCPA, which require companies to explain and justify their decisions.

Value

Improved decision making
Get more insight into the reasoning behind model predictions helping business leaders make better-informed decisions, leading to improved stakeholder confidence.

Reduced risk
Identify potential risks in decisions and take steps to reduce them to protect the business from costly legal and financial repercussions.

Faster development
Reduce the time it takes to develop complex models. By making models more interpretable, developers can quickly identify problems and make changes to improve their performance.

Global Interpretability

A comprehensive look into the key features influencing the model outcomes while also emphasizing on a particular prediction made by the model.

Benefits

Enhanced trust
Be confident and demonstrate that the system is making reliable decisions and can be trusted.

Enhanced accountability
Provide transparency and accountability to stakeholders, improving business relationships.

Reduced legal risk
Identify potential bias or discriminatory behavior in a system, helping organizations mitigate legal risks.

Value

Improved trust
Stakeholders can trust the decisions made by the ML system, as they can easily understand and interpret the results.

Lower costs:
By using global interpretability understand how changes to the data can affect the model, thus reducing costs associated with model training and deployment.

Improved customer experience
Global interpretability, provides customers with more intuitive explanations of their decisions and allowing them to gain insights into their customers’ needs.

Model Evaluation

Visualise Key evaluation metrics along with model explanations to gain enhanced visibility into the ‘how’ and ‘why’ behind black-box models. Easy correlation between the performance and feature attributions for models through sharable Explainability reports.

Benefits

Improved Model Performance:
Evaluating a model helps identify its strengths and weaknesses, which can then be used to improve it.

 Better Understanding of Data:
Evaluating a model provides insights into the relationship between the features and target variable.

Better Model Selection:
Model evaluation in Giggso with downloadable reports helps in comparing different models and selecting the best one for a given problem.

Value

Increased Confidence
Evaluating a model provides evidence that it will perform well in real-world applications, increasing confidence in its deployment.

Data Characteristics Explained:
Model evaluation helps understand the patterns and relationships in the data, allowing for more informed decisions.

Improved Model Deployment:
By evaluating the model, Giggso ensures that the model is ready for deployment and will perform well in real-world applications for customers.

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