文件名称：Go-leaves是GBRT模型预测代码的纯Go实现库
文件大小：607KB
文件格式：ZIP
更新时间：2022-09-02 21:08:33
Go开发-机器学习库
leaves 是 GBRT (Gradient Boosting Regression Trees) 模型预测代码的纯Go实现库
【文件预览】：
dmitryikh-leaves-ea11ec1
----.travis.yml(152B)
----testdata()
--------lg_dart_breast_cancer.json(94KB)
--------kddcup99_test.tsv(66KB)
--------xgdermatology_true_predictions.txt(16KB)
--------lgmulticlass_true_raw_predictions.txt(49KB)
--------tree_2leaves.txt(144B)
--------xg_dart_agaricus.model(18KB)
--------agaricus_test.libsvm(179KB)
--------iris.py(782B)
--------lgmulticlass.model(127KB)
--------iris_lightgbm_rf.py(847B)
--------breast_cancer_test.tsv(42KB)
--------sk_gradient_boosting_classifier.model(84KB)
--------densemat.libsvm(37B)
--------dermatology_test.libsvm(6KB)
--------lg_dart_breast_cancer.model(20KB)
--------iris_test.libsvm(750B)
--------sk_gradient_boosting_classifier_test.libsvm(212KB)
--------xgagaricus_true_predictions.txt(39KB)
--------lg_kddcup99.model(319KB)
--------xgdermatology.model(14KB)
--------lgmulticlass_true_predictions.txt(49KB)
--------xgblin_agaricus.model(831B)
--------lg_rf_iris.model(10KB)
--------xgagaricus.model(1KB)
--------tree_1leaf.txt(194B)
--------xgblin_agaricus_true_predictions.txt(39KB)
--------lg_1tree.json(1KB)
--------sk_gradient_boosting_classifier_true_predictions.txt(12KB)
--------xg_dart_agaricus_true_predictions.txt(40KB)
--------model_simple.txt(3KB)
--------lg_kddcup99.py(3KB)
--------xgblin_agaricus_true_raw_predictions.txt(40KB)
--------lg_dart_breast_cancer.py(801B)
--------lg_rf_iris_true_predictions.txt(750B)
--------csrmat.libsvm(33B)
--------lg_kddcup99_true_predictions.txt(166KB)
--------sk_iris_true_predictions.txt(2KB)
--------tree_3leaves.txt(208B)
--------README.md(10KB)
--------lg_1tree_1leaf.json(321B)
--------sk_iris.model(126KB)
--------multiclass_test.tsv(90KB)
--------lg_dart_breast_cancer_true_predictions.txt(1KB)
----benchmark()
--------lg.py(2KB)
--------all.sh(1KB)
--------xg.py(2KB)
----leaves_test.go(28KB)
----lgtree.go(3KB)
----mat()
--------mat_test.go(3KB)
--------mat.go(2KB)
--------mat_io.go(7KB)
----lgensemble.go(2KB)
----skensemble_io.go(6KB)
----internal()
--------pickle()
--------xgbin()
----doc.go(6KB)
----xgblinear_io.go(2KB)
----xgensemble_io.go(7KB)
----lgensemble_test.go(7KB)
----xgblinear.go(1KB)
----transformation()
--------transformation.go(838B)
--------raw.go(474B)
--------softmax.go(683B)
--------logistic.go(635B)
----NOTES.md(1KB)
----LICENSE.md(1KB)
----logo.png(59KB)
----xgensemble.go(1KB)
----testscripts()
--------doctest.py(9KB)
----README.md(5KB)
----util()
--------util_test.go(5KB)
--------util.go(7KB)
----leaves.go(8KB)
----lgensemble_io.go(19KB)