Daisy_fight的博客

KNN(classic,simple,easy to understand)from sklearn.neighbors import KNeighborsClassifierclf = KNeighborsClassifier()clf.fit(features_train, labels_train) clf.predict(features_test)acc = clf.score(...

决策树编码#classifyDT.pydef classify(features_train, labels_train): ### your code goes here--should return a trained decision tree classifer from sklearn import tree clf = tree.DecisionTr...

SVMfrom class_vis import prettyPicturefrom prep_terrain_data import makeTerrainDataimport matplotlib.pyplot as pltimport copyimport numpy as npimport pylab as plfeatures_train, labels_train, ...

#main.py""" Complete the code in ClassifyNB.py with the sklearn Naive Bayes classifier to classify the terrain data. The objective of this exercise is to recreate the decision boun...

特征选择sklearn 中有两大单变量特征选择工具：SelectPercentile 和 SelectKBest。 两者之间的区别从名字就可以看出：SelectPercentile 选择最强大的 X% 特征（X 是参数），而 SelectKBest 选择 K 个最强大的特征（K 是参数）。from sklearn.feature_selection import SelectPercentile...

特征缩放机器学习算法会受到特征缩放的影响？使用 RBF 核函数的 SVM和K-均值聚类sklearnfrom sklearn.preprocessing import MinMaxScalerimport numpyweights = numpy.array([[115.],[140.],[175.]])scaler = MinMaxScaler()rescaled_weight = sc...

from sklearn.cluster import KMeanskmeans = KMeans(n_clusters=2).fit(X)kmeans.predict(X)n_clusters : The number of clusters to form as well as the number of centroids to generate.#分为几类n_init : Number...

##带有异常值的回归斜率from sklearn import linear_modelreg = linear_model.LinearRegression()reg.fit(ages_train, net_worths_train)print(reg.coef_)##带有异常值的回归分数print(reg.score(ages_test, net_worths_test))##清理后的斜...

##安然数据集的大小print(len(enron_data))##安然数据集中的特征print(len(enron_data["SKILLING JEFFREY K"]))##在安然数据中查找 POIprint(len(dict ((key,value) for key,value in enron_data.items() if value['poi']==1)))##存在多少 POI？wi...

#studentRegression.pydef studentReg(ages_train, net_worths_train): ### import the sklearn regression module, create, and train your regression ### name your regression reg ### your c...