catboost

Python Catboost: Multiclass F1 score custom metric

由 天大地大妈咪最大 提交于 2021-02-11 05:15:51
问题 How do you find the F1-score for each class of a multiclass Catboost Classifier? I've already read through the documentation and the github repo where someone asks the same question. However, I am unable to figure out the codesmithing to achieve this. I understand that I must use the custom_metric parameter in CatBoostClassifier() but I don't know what arguments are acceptable for custom_metric when I want F1 score for each class of my multiclass dataset. Suppose you have a toy dataset (from

Python Catboost: Multiclass F1 score custom metric

由 本小妞迷上赌 提交于 2021-02-11 05:06:38
问题 How do you find the F1-score for each class of a multiclass Catboost Classifier? I've already read through the documentation and the github repo where someone asks the same question. However, I am unable to figure out the codesmithing to achieve this. I understand that I must use the custom_metric parameter in CatBoostClassifier() but I don't know what arguments are acceptable for custom_metric when I want F1 score for each class of my multiclass dataset. Suppose you have a toy dataset (from

Python Catboost: Multiclass F1 score custom metric

由 ▼魔方 西西 提交于 2021-02-11 05:06:31
问题 How do you find the F1-score for each class of a multiclass Catboost Classifier? I've already read through the documentation and the github repo where someone asks the same question. However, I am unable to figure out the codesmithing to achieve this. I understand that I must use the custom_metric parameter in CatBoostClassifier() but I don't know what arguments are acceptable for custom_metric when I want F1 score for each class of my multiclass dataset. Suppose you have a toy dataset (from

Python Catboost: Multiclass F1 score custom metric

由 僤鯓⒐⒋嵵緔 提交于 2021-02-11 05:04:32
问题 How do you find the F1-score for each class of a multiclass Catboost Classifier? I've already read through the documentation and the github repo where someone asks the same question. However, I am unable to figure out the codesmithing to achieve this. I understand that I must use the custom_metric parameter in CatBoostClassifier() but I don't know what arguments are acceptable for custom_metric when I want F1 score for each class of my multiclass dataset. Suppose you have a toy dataset (from

How to create custom eval metric for catboost?

由 时间秒杀一切 提交于 2021-02-07 18:39:14
问题 Similar SO questions: Python Catboost: Multiclass F1 score custom metric Catboost tutorials https://catboost.ai/docs/concepts/python-usages-examples.html#user-defined-loss-function Question In this question, I have a binary classification problem. After modelling we get the test model predictions y_pred and we already have true test labels y_true . I would like to get the custom evaluation metric defined by following equation: profit = 400 * truePositive - 200*fasleNegative - 100

Plot Learning Curve of CatBoostClassifier with Yellowbrick

由 不羁的心 提交于 2020-12-15 06:50:54
问题 I'm trying to plot a learning curve for the CatBoostClassifier. The error occurs when I fit the CatBoostClassifier into LearningCurve from yellowbrick. I think this should work since CatBoost is sklearn compatible and yellow brick is a sklearn extension. Code snippet: kf = RepeatedStratifiedKFold(n_splits=10, n_repeats=3, random_state=0) sizes = np.linspace(0.2, 1.0, 10) estimator = CatBoostClassifier( iterations=42, learning_rate=0.3, max_depth=10) visualizer = LearningCurve( estimator, cv

PyCaret 2.1横空出世-有什么新的内容？

由 瘦欲@ 提交于 2020-10-23 01:20:58
2020年8月PyCaret2.1 更新版本正式发布。 Py Caret是一个开源的、低代码率的Python机器学习库，它可以使机器学习工作流程自动化，同时，它也是一个端到端的机器学习和模型管理工具，可以缩短机器学习实验周期，将生产力提高10倍。 与其他开源机器学习库相比，Py Caret是低代码库的一个很好的选择，只利用几个单词，便可以用它来替换数百行代码，从而使得实验快速高效。 如果以前没有听到或使用过PyCaret，请参阅先前发布的指南，以便快速入门。 安装PyCaret 安装Py Caret非常容易，只需要几分钟的时间。建议使用虚拟环境来避免与其他库的潜在冲突。请参阅下面的示例代码，以创建Conda环境并在该Conda环境中安装pycaret： #创建conda环境 conda create --name yourenvname python=3.6 #激活环境 conda activate yourenvname #安装pycaret pip install pycaret #创建与conda环境链接的notebook内核 python -m ipykernel install --user --name yourenvname --display-name "display-name" 如果已经安装好了PyCaret，还可以使用pip对它更新： pip install

Catboost 一个超级简单实用的boost算法

由 心已入冬 提交于 2020-10-06 06:43:29
今天笔者来介绍一个超级简单并且又极其实用的boosting算法包Catboost，据开发者所说这一boosting算法是超越Lightgbm和XGBoost的又一个神器。 catboost 简介 在笔者看来catboost有一下三个的优点： 它自动采用特殊的方式处理 类别型特征（categorical features） 。首先对categorical features做一些统计，计算某个类别特征（category）出现的频率，之后加上超参数，生成新的数值型特征（numerical features）。这也是我在这里介绍这个算法最大的motivtion，有了catboost，再也 不用手动处理类别型特征了。 catboost还使用了 组合类别特征 ，可以利用到特征之间的联系，这极大的 丰富了特征维度 。 catboost的基模型采用的是 对称树 ，同时计算leaf-value方式和传统的boosting算法也不一样，传统的boosting算法计算的是平均数，而catboost在这方面做了优化采用了其他的算法，这些改进都能 防止模型过拟合 。 catboost 实战 这里笔者采用的是之前参加一个CTR点击率预估的数据集，首先通过pandas读入数据。 from catboost import CatBoostClassifier import pandas as pd from

Catboost plot_tree understanding

由 风格不统一 提交于 2020-08-26 06:57:46
问题 When plotting a tree from catboost, it shows val in leaves; what do these values represent? I can't find the answer in their official tutorial on plotting, nor are there any such questions answered anywhere that I could find. Like: LightGBM plot_tree() Leaf numbers What' the meaning of "Val" in the visualization of a lightgbm tree? https://github.com/catboost/catboost/issues?q=plot_tree 来源： https://stackoverflow.com/questions/63407613/catboost-plot-tree-understanding

Catboost plot_tree understanding

由 我是研究僧i 提交于 2020-08-26 06:57:46
问题 When plotting a tree from catboost, it shows val in leaves; what do these values represent? I can't find the answer in their official tutorial on plotting, nor are there any such questions answered anywhere that I could find. Like: LightGBM plot_tree() Leaf numbers What' the meaning of "Val" in the visualization of a lightgbm tree? https://github.com/catboost/catboost/issues?q=plot_tree 来源： https://stackoverflow.com/questions/63407613/catboost-plot-tree-understanding
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