1.2 sklearn 中决策树 模块sklearn.tree sklearn 中鄋的决策树的类都在 tree 这个模块下 sklearn 建模基本流程 实例化 决策树 模型 通过模型接口,训练模型 导入测试集,从模型接口中 提取信息 from sklearn import tree # 导入模块 clf = tree.DecisionTreeClassifier() # 实例化 决策树 clf = clf.fit(X_t...
(2)朴素贝叶斯Naive Bayes (3)决策树 Decision Tree - ID3 - C4.5 -分类回归树Classification And Regression Tree (CART) 区别:[决策树系列算法总结(ID3, C4.5, CART, Random Forest, GBDT)][1] (4)支持向量机器 Support Vector Machine (SVM) ### 2.1.2 回归 Regression (1)线性回归 linear regression...
调用决策树分类器 fromsklearn.treeimportDecisionTreeClassifier dtc=DecisionTreeClassifier()dtc.fit(x_train,y_train) DecisionTreeClassifier(class_weight=None,criterion='gini',max_depth=None,max_features=None,max_leaf_nodes=None,min_impurity_decrease=0.0,min_impurity_split=None,min_samples_leaf=1,min...
from sklearn.tree import DecisionTreeClassifier from sklearn.ensemble import RandomForestClassifier from sklearn.datasets import load_wine # 导入数据集: wine = load_wine() wine.data wine.target # 建模的基本流程: from sklearn.model_selection import train_test_split Xtrain, Xtest, Ytrain, Ytest...
(class_weight=None, criterion='gini', max_depth=5, max_features='auto', max_leaf_nodes=None, min_impurity_decrease=0.0, min_impurity_split=None, min_samples_leaf=1, min_samples_split=2, min_weight_fraction_leaf=0.0, presort=False, random_state=705712365, splitter='best'), DecisionTree...
dtc=DecisionTreeClassifier()dtc.fit(x_train,y_train) 代码语言:javascript 复制 DecisionTreeClassifier(class_weight=None,criterion='gini',max_depth=None,max_features=None,max_leaf_nodes=None,min_impurity_decrease=0.0,min_impurity_split=None,min_samples_leaf=1,min_samples_split=2,min_weight_fractio...
import pandas as pd from sklearn.tree import DecisionTreeClassifier import matplotlib.pyplot as plt from sklearn.model_selection import GridSearchCV #
sklearn.datasets.load_iris — scikit-learn documentation X,y=load_iris(return_X_y=True) #效果等同于 data=load_iris() X=data.data y=data.target #由于Bunch对象的特性,可以用字典方式访问 X=data['data'] y=data['target'] # # 导出为pandas dataframe: ...
Decision Tree Random Forest Logistic Regression Support Vector Machine 新版Notebook- BML CodeLab上线,fork后可修改项目版本进行体验 sklearn之分类算法与手写数字识别 sklearn是Python的一个机器学习的库,它有比较完整的监督学习与非监督学习的模型。本文将使用sklearn库里的分类模型来对手写数字(MNIST)做分类实践。
版权声明：本文内容由互联网用户自发贡献，该文观点仅代表作者本人。本站仅提供信息存储空间服务，不拥有...