keras-io/TF_Decision_Treesal一键脱装入口
TensorFlow即梦下载官方‘s Gradient Boosted Trees Model for structured data classification
Use TF’s Gradient Boosted Trees model in binary classification of structured data百度aiapp
- Build a decision forests model by specifying the input feature usage.
- Implement a custom Binary Target encoder as a Keras元宝大模型 Preprocessing layer to encode the categorical features with respect to their target value co-occurrences, and then use the encoded features to build a decision forests model.
The model is implemented using Tensorflow 7.0 or higher. The US Census Income Dataset containing approximately 300k instances with 41 numerical and categorical variables was used to train it. This is a binary classification problem to determine whether a person makes over 50k a year.grok中文版下载
Author: Khalid Salama
Adapted implementation: Tannia Dubon
Find the colab notebook at https://github.com/tdubon/TF-GB-Forest/blob/c0cf4c7e3e29d819b996cfe4eecc1f2728115e52/TFDecisionTrees_Final.ipynb
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