from sklearn.neighbors import KNeighborsClassifier as KNN from sklearn.model_selection import train_test_split from sklearn.metrics import accuracy_score from sklearn.model_selection import GridSearchCV from sklearn import datasets #导入数据集模块 from sklearn.metrics import classification_report #用于...
#使用sklearn的kNN算法 import numpy as np from sklearn.neighbors import KNeighborsClassifier #包装了KNN算法 raw_data_X = [[1.232422,1.22324], [2.324232,1.3224], [2.3435353,2.3232342], [3.434353,3.434353], [4.54546,3.54544], [7.42422,6.764353], [6.42224534,7.533232], [8.435353,8.5433], [9.423534...
importnumpy as npimportmatplotlib.pyplot as plt#导入KNN分类器fromsklearn.neighborsimportKNeighborsClassifierfromsklearnimportdatasetsfromsklearn.model_selectionimporttrain_test_split#载入鸢尾花数据集#iris是一个对象类型的数据,其中包括了data(鸢尾花的特征)和target(也就是分类标签)iris =datasets.load_iris()#...
knn=KNeighborsClassifier()# 进行填充测试数据进行训练 knn.fit(X_train,y_train)params=knn.get_params()print(params) 输出如下: {‘algorithm’: ‘auto’, ‘leaf_size’: 30, ‘metric’: ‘minkowski’, ‘metric_params’: None, ‘n_jobs’: None, ‘n_neighbors’: 5, ‘p’: 2, ‘weights...
KNN_classifier.fit(train_x, train_y) # 传入测试样本数据进行预测,并返回预测结果 KNN_classifier.predict(test_x) 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. View Code 三、sklearn使用train_test_split来测试模型的性能(iris鸢尾花数据)
SomeClassifier = RandomForestClassifier SomeRegressor = LinearRegression SomeModel = KMeans, PCA SomeModel = GridSearchCV, OneHotEncoder 上面具体化的例子分别是随机森林分类器、线性回归器、K 均值聚类、主成分分析、网格追踪法、独热编码。
from sklearn import neighbors, datasets iris = datasets.load_iris() X, y = iris.data, iris.target # create the model knn = neighbors.KNeighborsClassifier(n_neighbors=5) # fit the model knn.fit(X, y) # What kind of iris has 3cm x 5cm sepal and 4cm x 2cm petal? # call the "...
KNNImputer使用k-最近邻算法来找到缺失值的最佳替代值: from sklearn.impute import KNNImputer # Code taken from Sklearn user guide X = [[1, 2, np.nan], [3, 4, 3], [np.nan, 6, 5], [8, 8, 7]] imputer = KNNImputer(n_neighbors=2) ...
pythonrandom-forestpandas-dataframehistogramcross-validationdata-visualizationnaive-bayes-classifierdimensionality-reductionlogistic-regressionmatplotlibmissing-datadata-preprocessingclass-imbalancesvm-classifiermultilayer-perceptroncategorical-dataroc-aucknn-classifierbank-marketing-analysissklearn-library ...
I'm trying to load an older Scikit-Learn KNN classifier model with pickle, but it's throwing the error: No module named 'sklearn.neighbors.classification', despite the fact that I have thelatest versionof scikit-learn installed and imported. ...