Explainability | Stardat

Explainability in one Minute

1 min

Investigating Features Interaction with ALE

Investigating the nature of interaction between two features and its effect on a model’s prediction might provide insightful knowledge ab...

1 min

Working Point

Working point is an easy knob to use in order to optimize the model performance to fit our needs. Working point (WP) is a value between 0...

1 min

Categorical Features Table

The categorical features table summarizes multiple statistics about every categorical feature in the data, allowing it to be investigated...

2 min

Feature Interaction

Features often interact with each other under model predictions, and therefore interaction analysis can provide meaningful insights for t...

1 min

Numerical Features Table

The numerical features table summarizes multiple statistics about every numerical feature in the data, allowing it to be investigated all...

1 min

Features Shared Distribution

Shared distribution heatmap is a very useful and visual way to examine the spread and legitimacy of the data and understand how different...

1 min

Feature Histogram

Feature histogram enables a single glance to view each features general distribution split between the labels categories. For continuous ...

1 min

Feature Leakage

The feature leakage ROC plot is a graphic way to evaluate the potential leakage there might be between each feature and the label. Data l...

1 min

Labels Distribution

The label distribution pie chart gives us a quick way to understand the balance of labels in the data, identifying potential unbalancness...

1 min

Precision-Recall Curve

Precision-Recall Curve is a graphic way to evaluate the model performance and trade-offs under different working points. Precision is a r...

1 min

Confusion Matrix

Confusion Matrix is a table that describes the performance of a classification model on a set of test data for which the true values are ...

1 min

Counterfactual Analysis

Counterfactuals provide an easy to understand local explanation to models prediction using a counter example providing a what-if intuitio...

1 min

Anchor Analysis

Anchors provide an intuitive set of rules that emphasis the features that are locally sufficient for the model to make a decision. These ...

1 min

Dependence Plot Per Feature

The partial dependence plot (PDP) shows the marginal effect one or two features have on the predicted outcome of a machine learning model...

1 min

Prediction Histogram

A prediction histogram is an intuitive graphic way for visualizing model predictions and the separation it achieves for the actual labels...

1 min

Force Plot

Force plots are a very intuitive and visual way to understand the influence of each feature on the models prediction for a specific insta...

2 min

Calibration Plot

Calibration plots give us a snapshot to understand how well a model's prediction correlate with a measure of probability that it is corre...

2 min

Receiver Operating Characteristic (ROC) Curve

Receiver Operating Characteristic Curve is a graphic way to evaluate the model performance and the trade-offs under different working poi...

1 min

Feature Importance

Feature Importance plots are a great way to get a sense quickly how much a model is relying on each feature to make it predictions. Featu...

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