CatBoost: Open-Source Tool That Tames Categorical Data and Speeds Up Predictions
Meet CatBoost, a new open-source tool that learns from data and works well with columns full of names or labels, called categorical features. It often gives better quality predictions than other tools on many public tests, and it does it using clever tricks. the makers built parts that run on a GPU and parts that run on a CPU, so training and making results finishes much quicker, sometimes way faster then the rest. You don’t need deep know-how to try it, it is ready to use and fast, people who tried it noticed it handle categories with less fuss. This means less time waiting and more time using the results, great for projects big or small. CatBoost is easy to install and start, it…
CatBoost: Open-Source Tool That Tames Categorical Data and Speeds Up Predictions
Meet CatBoost, a new open-source tool that learns from data and works well with columns full of names or labels, called categorical features. It often gives better quality predictions than other tools on many public tests, and it does it using clever tricks. the makers built parts that run on a GPU and parts that run on a CPU, so training and making results finishes much quicker, sometimes way faster then the rest. You don’t need deep know-how to try it, it is ready to use and fast, people who tried it noticed it handle categories with less fuss. This means less time waiting and more time using the results, great for projects big or small. CatBoost is easy to install and start, it will surprise you, and it might be the tool you pick next time you want reliable answers from messy data.
Read article comprehensive review in Paperium.net: CatBoost: gradient boosting with categorical features support
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