Tutorials¶
Basic¶
It is better to start scikit-uplift from the basic tutorials.
The overview of the basic approaches to solving the Uplift Modeling problem¶
In English 🇬🇧 |
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In Russian 🇷🇺 |
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Uplift modeling metrics¶
In English 🇬🇧 |
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Example of usage model from sklift.models in sklearn.pipeline¶
In English 🇬🇧 |
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In Russian 🇷🇺 |
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Example of usage model from sklift.models in sklearn.model_selection¶
In English 🇬🇧 |
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Exploratory data analysis¶
The package contains various public datasets for uplift modeling. Below you find jupyter notebooks with EDA of these datasets and a simple baseline.
EDA of Lenta dataset |
In English 🇬🇧 |
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EDA of X5 dataset |
In English 🇬🇧 |
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EDA of Criteo dataset |
In English 🇬🇧 |
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EDA of Hillstrom dataset |
In English 🇬🇧 |
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EDA of Megafon dataset |
In English 🇬🇧 |
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