Remove 2009 Remove Metrics Remove Predictive Modeling Remove Testing
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Explaining black-box models using attribute importance, PDPs, and LIME

Domino Data Lab

Model distillation – this approach builds a separate explainable model that mimics the input-output behaviour of the deep network. Because this separate model is essentially a white-box, it can be used for extraction of rules that explain the decisions behind the ANN. Creating a PDP for our model is fairly straightforward.

Modeling 139
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Credit Card Fraud Detection using XGBoost, SMOTE, and threshold moving

Domino Data Lab

from sklearn import metrics. This is to prevent any information leakage into our test set. 2f%% of the test set." 2f%% of the test set." Fraudulent transactions are 0.17% of the test set. 2f%% of the test set." Fraudulent transactions are 50.00% of the test set. Model training.

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6 Case Studies on The Benefits of Business Intelligence And Analytics

datapine

Everything is being tested, and then the campaigns that succeed get more money put into them, while the others aren’t repeated. This methodology of “test, look at the data, adjust” is at the heart and soul of business intelligence. 5) Find improvement opportunities through predictions. A great use case of this benefit is Uber.