简介:Python实现Catboost分类模型(CatBoostClassifier算法)项目实战 说明:这是一个机器学习实战项目(附带数据+代码+文档+视频讲解),如需数据+代码+文档+视频讲解可以直接到文章最后获取。 1.项目背景 CatBoost提供最先进的结果,在性能方面与任何领先的机器学习算法相比都具有竞争力。CatBoost是一种基于对称决策树(oblivious...
from catboost import CatBoostClassifier # 创建模型 model = CatBoostClassifier(iterations=100, learning_rate=0.1, depth=6, loss_function='Logloss') # 训练模型 model.fit(X_train, y_train, cat_features=df.select_dtypes(include=["object"]).columns) 5. 评估模型 评估模型在测试集上的性能。 from...
CatBoostClassifier(eval_metric="AUC", depth=4, iterations=500, l2_leaf_reg=9, learning_rate=0.15) clf.fit(train, y_train) print(auc(clf, train, test)) # (0.7809684655761157, 0.7104617034553192) (3)有Categorical features选项的代码 import pandas as pd, numpy as np from sklearn.model_...
SageMaker CatBoost uses the catboost.CatBoostClassifier and catboost.CatBoostRegressor modules to serialize or deserialize the model, which can be used for saving or loading the model. To use a model trained with SageMaker CatBoost with catboost Use the following Python code: import tarfile from catbo...
fromcatboostimportCatBoostClassifier fromsklearn.preprocessingimportLabelEncoder importgc importos fromsklearn.metricsimportprecision_score,recall_score,f1_score importxgboostasxgb importwarnings warnings.filterwarnings("ignore") importjieba importmatplotlib.pyplotasplt ...
from catboost import CatBoostClassifier #pip3 install --user catboost -i https://pypi.tuna.tsinghua.edu.cn/simple/ #%% train = pd.read_csv('D:/python_home/阿⾥云⾦融风控-贷款违约预测/train.csv')testA = pd.read_csv('D:/python_home/阿⾥云⾦融风控-贷款违约预测/testA.csv')#%%...
fromcatboostimportCatBoostClassifier# 定义模型model = CatBoostClassifier(iterations=100, learning_rate=0.1, loss_function='Logloss')# 拟合模型model.fit(X_train, y_train, cat_features=categorical_features_indices) 3. 使用CatBoost的自动分类特征处理 ...
Create the object of the CatBoost Classifier model You can also add other parameters and test your code here Some parameters are : l2_leaf, model_size Documentation of sklearn CatBoostClassifier: https://catboost.ai/docs/concepts/python-reference_catboostclassifier.html ...
Problem: CatBoostClassifier throws error for simple binary classification Reproducible code: import numpy as np from catboost import CatBoostClassifier X = np.array([[1, 1], [1, 2], [1, 3], [2, 1], [2, 2], [2, 3]]) y = np.array([1, 1, 1,...
model = CatBoostClassifier(iterations=1000, task_type="GPU", devices='0') model.fit(train_data, train_labels, verbose=False) 安装支持GPU示例 https://catboost.ai/docs/concepts/python-installation.htmlGPU system requirements 应用场景 作为GBDT框架内的算法,GBDT、XGBoost、LightGBM能够应用的场景CatBoost也...