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1 %matplotlib notebook 2 3 import networkx as nx 4 import matplotlib.pyplot as plt 5 6 # 数据读取 7 G = nx.read_gpickle('major_us_cities') 1 # draw the graph using the default spring layout 2 plt.fig... 阅读全文
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邻接表 G_adjlist.txt is the adjaceny list representation of G1. It can be read as follows: 0 1 2 3 5 →→ node 0 is adjacent to nodes 1, 2, 3, 5 1 3 6 →→ n 阅读全文
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CountVectorizer AUC: 0.889951006492 AUC: 0.889951006492 AUC: 0.889951006492 AUC: 0.889951006492 AUC: 0.889951006492 1 feature_names = np.array(vect.ge 阅读全文
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1 import nltk 2 from nltk.book import * *** Introductory Examples for the NLTK Book *** Loading text1, ..., text9 and sent1, ..., sent9 Type the name 阅读全文
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1 import pandas as pd 2 3 time_sentences = ["Monday: The doctor's appointment is at 2:45pm.", 4 "Tuesday: The dentist's appointment is at 11:30 am.", 5 "Wed... 阅读全文
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['#UNSG'] ['#UNSG'] ['#UNSG'] ['#UNSG'] ['#UNSG'] 1 [w for w in text6 if w.startswith('@')] ['@'] 1 text7 = '@UN @UN_Women "Ethics are built right int 阅读全文
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这本笔记本的目的是让你可视化各种分类器的决策边界。 本笔记本中使用的数据基于存储在mushrooms.csv中的UCI蘑菇数据集。 为了更好地确定决策边界，我们将对数据执行主成分分析（PCA）以将维度降至2维。 降维将在本课程后面的模块中介绍。 玩弄不同的模型和参数，看看它们如何影响分类器的决策边界 阅读全文