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Explaining black-box models using attribute importance, PDPs, and LIME

Domino Data Lab

In this article we cover explainability for black-box models and show how to use different methods from the Skater framework to provide insights into the inner workings of a simple credit scoring neural network model. The interest in interpretation of machine learning has been rapidly accelerating in the last decade.

Modeling 139
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Business Intelligence System: Definition, Application & Practice

FineReport

In addition, data warehouse provides a data storage environment where data onto multiple data sources will be ETLed(Extracted, Transformed, Dunked) , cleaned up, and stored on a specific topic, indicating powerful data integration and maintenance capabilities of BI. Data Analysis. Data Mining.

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How Do Super Rookies Start Learning Data Analysis?

FineReport

For super rookies, the first task is to understand what data analysis is. Data analysis is a type of knowledge discovery that gains insights from data and drives business decisions. One is how to gain insights from the data. Data is cold and can’t speak. 6 Key Skills That Data Analysts Need to Master.

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ML internals: Synthetic Minority Oversampling (SMOTE) Technique

Domino Data Lab

In this article we discuss why fitting models on imbalanced datasets is problematic, and how class imbalance is typically addressed. Data mining for direct marketing: Problems and solutions. Proceedings of the Fourth International Conference on Knowledge Discovery and Data Mining, 73–79.

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Changing assignment weights with time-based confounders

The Unofficial Google Data Science Blog

Companies like Google [2], Amazon [3], and Microsoft [4] have all published scholarly articles on this topic. In practice, one may want to use more complex models to make these estimates. For example, one may want to use a model that can pool the epoch estimates with each other via hierarchical modeling (a.k.a.