RMySQL
catboost
| RMySQL | catboost | |
|---|---|---|
| 1 | 8 | |
| 207 | 7,767 | |
| 0.5% | 0.8% | |
| 4.7 | 9.9 | |
| 5 months ago | 1 day ago | |
| C | Python | |
| - | Apache License 2.0 |
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RMySQL
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How to convert Blob from SQL to string?
Google came up with this, though I can't say it really looks like a likely winner.
catboost
- CatBoost: Open-source gradient boosting library
- Boosting Algorithms
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What's New with AWS: Amazon SageMaker built-in algorithms now provides four new Tabular Data Modeling Algorithms
CatBoost is another popular and high-performance open-source implementation of the Gradient Boosting Decision Tree (GBDT). To learn how to use this algorithm, please see example notebooks for Classification and Regression.
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Writing the fastest GBDT libary in Rust
Here are our benchmarks on training time comparing Tangram's Gradient Boosted Decision Tree Library to LightGBM, XGBoost, CatBoost, and sklearn.
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Data Science toolset summary from 2021
Catboost - CatBoost is an open-source software library developed by Yandex. It provides a gradient boosting framework which attempts to solve for Categorical features using a permutation driven alternative compared to the classical algorithm. Link - https://catboost.ai/
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CatBoost Quickstart — ML Classification
CatBoost is an open source algorithm based on gradient boosted decision trees. It supports numerical, categorical and text features. Check out the docs.
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[D] What are your favorite Random Forest implementations that support categoricals
If you considering GBDT check out catboost, unfortunately RF mode is not available but library implement lots of interesting categorical encoding tricks that boost accuracy.
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CatBoost and Water Pumps
The data contains a large number of categorical features. The most suitable for obtaining a base-line model, in my opinion, is CatBoost. It is a high-performance, open-source library for gradient boosting on decision trees.
What are some alternatives?
mydumper - Official MyDumper project [Moved to: https://github.com/mydumper/mydumper]
xgboost - Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow
mydumper - Official MyDumper Project
Recommender - A C library for product recommendations/suggestions using collaborative filtering (CF)
Collapse Launcher - An Advanced Launcher for miHoYo Games
Keras - Deep Learning for humans
jsonlite - A Robust, High Performance JSON Parser and Generator for R
Prophet - Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
qs - Quick serialization of R objects
vowpal_wabbit - Vowpal Wabbit is a machine learning system which pushes the frontier of machine learning with techniques such as online, hashing, allreduce, reductions, learning2search, active, and interactive learning.
kunlun - KunlunBase is a distributed relational database management system(RDBMS) with complete NewSQL capabilities and robust transaction ACID guarantees and is compatible with standard SQL. Applications which used PostgreSQL or MySQL can work with KunlunBase as-is without any code change or rebuild because KunlunBase supports both PostgreSQL and MySQL connection protocols and DML SQL grammars. MySQL DBAs can quickly work on a KunlunBase cluster because we use MySQL as storage nodes of KunlunBase. KunlunBase can elastically scale out as needed, and guarantees transaction ACID under error conditions, and KunlunBase fully passes TPC-C, TPC-H and TPC-DS test suites, so it not only support OLTP workloads but also OLAP workloads. Application developers can use KunlunBase to build IT systems that handles terabytes of data, without any effort on their part to implement data sharding, distributed transaction processing, distributed query processing, crash safety, high availability, strong consistency
mxnet - Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more